Conventional fat quantification methods for rotator cuff muscles have various limitations, such as inconsistent reliabilities of the Goutallier grades and need for advanced techniques in quantitative MRI sequences. We aimed to examine a threshold-based fat quantification method in the supraspinatus muscle on standard T1-weighted MR images and compare the threshold-based method with Goutallier grades and MR spectroscopy.We retrospectively examined 38 symptomatic patients, who underwent T1 and T2-weighted fast spin-echo MR imaging and a single voxel spin-echo MR spectroscopy. The supraspinatus muscle and fossa were manually segmented in T1-weighted sagittal images and clustering-based thresholding was applied to quantify the fat fractions in the segmented areas using custom MATLAB software. Threshold-based fat fractions were compared with the Goutallier grades and MR spectroscopy fat/water ratios. A one-way analysis of variance and Pearson correlation were tested in the MATLAB software.p < 0.001). Threshold-based fat fractions in the supraspinatus muscle strongly correlated with the MR spectroscopy fat/water ratio (Pearson correlation R-square = 0.83).Inter-observer reliability of threshold-based fat fractions for the supraspinatus muscle and fossa were 0.977 and 0.990 respectively, whereas the reliability of the Goutallier grading was 0.798. Threshold-based fat fractions in the supraspinatus fossa were significantly different between various Goutallier grades (one-way ANOVA, Threshold-based fat quantification on standard T1-weighted MR images was highly reliable and produced comparable results to conventional Goutallier grades and MR spectroscopy fat/water ratios and could serve as an alternative method for accurate fat quantification in rotator cuff muscles. Fatty infiltration and atrophy of the rotator cuff muscles have been thought to be secondary signs of chronic stages of muscle tears and pose a potential risk of re-tears after repair surgeries. Although some studies have reported delayed fatty degenerations after successful repairs, fatty infiltration and atrophy of the rotator cuff muscles have been known to be irreversible and may result in pathologic conditions of the glenohumeral joint, such as rotator cuff arthropathies –3. Thus,The Goutallier classification has been the most popular method to evaluate the quality of rotator cuff muscles before surgery. The Goutallier method was originally designed as a semi-quantitative grading system of degenerative rotator cuff muscles with five different grades from grade 0 (no fat inside the muscle) to grade 4 (more than 50% fat inside the muscle) in CT images. Currently, a similar grading system is widely applied in MR images –10. The Recently, the single-voxel proton MR spectroscopy (MRS) was shown to produce accurate and reliable measurements of the fat content in the rotator cuff muscles by comparing the strength of the fat and water signals in the frequency domain of MR images , 16. HowAlthough MR spectroscopy and Dixon-based MRI have been studied as an accurate and reliable estimation of the fat fraction in muscle tissues by using the unique magnetic relaxation characteristics of the fat and water molecules, these techniques are not commonly used in daily clinical practice because substantial technical efforts are required for additional imaging procedures. Thus, a reliable and technically simple fat quantification method on standard T1-weighted MR images would allow an easy assessment of the degree of fatty degeneration in muscle tissues for small clinics with limited imaging resources. In this study, we aimed to quantify the fat content of the supraspinatus muscle on existing standard T1-weighted MR images by applying image thresholding techniques. Then, the threshold-based quantification results were compared with the conventional Goutallier classifications and MRS fat/water ratios to examine whether the new threshold-based approach is correlated with previously established methods. This new method may result in early diagnoses of muscle damages and improve surgical outcomes of repair surgeries.n = 3), surgery (n = 1), infection (n = 1), rheumatoid arthritis (n = 1), and congenital anomaly (n = 1) were excluded. MR images with artifacts from respiratory motion (n = 3) were also excluded. Finally, this study included 38 patients with 22 females  and 16 males . The ages of the female patients were significantly higher than those of the male patients . Supraspinatus pathology of the study population included normal (n = 4), tendinopathy (n = 6), articular-side low grade partial tears (n = 5), bursal-side high grade partial tears (n = 6), and full thickness tears (n = 17). A total of 16 patients eventually underwent rotator cuff repair surgeries. Inclusion criteria were patients with suspected rotator cuff pathology, possibly considering repair surgeries.This study was approved by the institutional review board, and informed consent was waived due to the retrospective nature of the study. We retrospectively examined the supraspinatus muscle on MR images of symptomatic patients from the outpatient shoulder clinic to evaluate the rotator cuff tendon status as well as muscle quality for preoperative evaluation. Total 48 patients were completed both proton MR spectroscopy and MR arthrography between January 2009 and December 2012. Patients with previous history of shoulder trauma (3) spin-echo proton MR spectroscopy without water saturation : 4000 ms, echo time (TE): 35 ms, bandwidth (BW): 2000, scan time: 3 min 20 s) was acquired at the center of the supraspinatus muscle at the site of the largest muscle cross-section prior to MR arthrography. The location of the voxel was manually determined by navigating the oblique coronal and sagittal MR images of the shoulder. Then, a Gaussian fit of the water and lipid peaks was performed to calculate the magnitude and location of the signals by using SpectroView software   with a flex-M shoulder array coil was used for the proton MR spectroscopy and MR arthrography. First, single voxel : 3–5) and T2-weighted fast spin-echo (FSE) sequence with and without fat suppression , oblique sagittal T1-weighted  and T2-weighted FSE sequence with fat suppression , and transverse T1-weighted FSE images with fat suppression .MR arthrography was obtained after intra-articular injection of 12 ml of gadodiamide  at a concentration of 2 mmol/L. Imaging protocol of MR arthrography was as follows: oblique coronal T1-weighted : 140 × 140 mmMultiple semi-quantitative MR-based Goutallier classifications were independently performed by three different raters. Examinations were done with oblique T1-weighted images at the location where the scapular spine meets the scapular neck and creates a “Y-shaped” bony configuration . PersonaOur threshold-based fat quantification method uses a clustering-based thresholding technique, which mathematically determines an optimal threshold value that separates the image pixels into foreground (bright) and background (dark) colors by analyzing the distribution of the pixel intensities within an image. We decided to use the Otsu thresholding , 26, whiThe threshold-based fat quantification method was tested in DICOM images. We measured the threshold-based fat fractions in 1) the supraspinatus muscle and 2) the supraspinatus fossa which were manually segmented in T1-weighted oblique sagittal images using a custom MATLAB  program .A one-way analysis of variance (ANOVA) was performed to compare the differences between various Goutallier grade groups. Post hoc comparisons between each Goutallier group were performed using the Tukey honest significant difference test. The inter-observer reliability of the Goutallier grading and threshold-based fat quantification was evaluated by calculating the inter-class correlation coefficient (ICC) with 95% confident interval (CI). The Pearson correlation coefficient (R) and R-squared value were calculated to determine the relationship between the MRS fat/water ratios and threshold-based fat fraction measurements. A The inter-observer reliability of the Goutallier grades between the three raters was fairly good with an ICC of 0.80 . The distribution of the final Goutallier graded in our population is presented in Table An example of threshold-based fat quantification is shown in Fig. p > 0.6, Fig. p < 0.02). However, the threshold-based fat fractions in the supraspinatus fossa exhibited significant differences between most Goutallier grades (p < 0.03), except for the pairs of grade 0 and 1 (p > 0.7) and grade 1 and 2 (p > 0.1).The mean fat fractions in the supraspinatus muscle and the supraspinatus fossa are listed in Table The fat/water ratio of MRS was correlated with the threshold-based fat fraction measurements in 1) the supraspinatus muscle and 2) the region of the supraspinatus fossa . Our study resulted in slightly better reliabilities and correlation coefficients than the values shown in a recent study that examined fuzzy C-means thresholding technique in freely available MIPAV  software to estimate the degree of fatty infiltration in various shoulder muscles in 7 subjects, and found excellent inter-observer reliabilities (ICC = 0.95) and correlations  with the fat fractions by six-point Dixon MRI . These rInter-observer variations in the manual segmentation were found to be approximately 4–9% of the mean segmented areas between different observers in supraspinatus muscle and fossa. Simple boundary shapes of supraspinatus muscle and fossa with circular and rounded triangular profiles might reduce the disagreement of segmentation lines between difference observers. Our intra-observer variations in the segmented areas (4–9%) would alter the final fat content by approximately 3–8% for a muscle with an 80% fat fraction. However, these changes in the fat content would be smaller in the muscles with lower fat fractions. Because most of our patients exhibited the fat contents much lower than 80%, the effect of segmentation errors on the final fat content estimations would be minimal.Differences in the threshold-based fat fraction of the supraspinatus fossa were found to be significant between different Goutallier grades, whereas the differences in the supraspinatus muscle fat content were minimal. Although the Goutallier grading system was designed to access the degree of fatty infiltration inside the rotator cuff muscles, our raters may consider a higher Goutallier grade for a patient with severe muscle atrophy because atrophy of the supraspinatus muscle is also believed to be an important sign of muscle degeneration. Our fat fraction measurements in the supraspinatus fossa would be similar to the conventional occupation ratio method which measures 2 dimensional areal ratios between the supraspinatus muscle and the supraspinatus fossa , 30. TheThe threshold-based fat fractions in the supraspinatus muscle exhibited a strong correlation with the MRS fat/water ratio . MR spectroscopy measures magnetic signals from various molecules in muscle tissues. Thus, the relative strength of the fat signal over the signals from other tissues is believed to provide an accurate proportion of the fat tissue inside the entire muscular structure. However, the relationship between the MRS fat/water ratios and the threshold-based fat fractions in the supraspinatus fossa were moderate because the MR spectroscopy only measured intramuscular fats within a single voxel of the supraspinatus muscle. A strong correlation between the threshold-based fat contents and MRS fat/water ratios suggests that majority of fat tissues in the supraspinatus muscle could be visually recognized by image thresholding techniques in standard T1-weighted images. Our study showed that the clustering-based thresholding technique could accurately estimate internal fat content of the supraspinatus muscle with high reliabilities without an aid of image post-processing software.2 dimensional assessments of muscular fatty degeneration in a single MR slide have been shown to inaccurately describe the true condition of an entire muscle. Because the fatty infiltration has been reported to be non-uniform throughout the muscle belly and the location of the single MR slide could be changed by muscle stretches after repair surgeries, 3 dimensional assessments of a whole muscle have been believed to significantly improve diagnostic outcomes. Unfortunately, current Goutallier classification method does not have established grading guidelines for multi-slide 3D images. A potential application of 3D Goutallier classification may require unacceptable amount of examination time for clinical applications. With the improvements of current automatic segmentation techniques, our threshold-based fat quantification method could be developed as a tool for the measurement of 3D fat content in a whole muscle to markedly improve the accuracy and reliability of clinical diagnosis on muscle degenerations.3 at the central portion of the supraspinatus muscle. Our spectroscopy measurements only provided limited information of the muscle composition within the small voxel, which may not reflect the condition of the whole muscle. Unfortunately, we were unable to apply a multi-voxel SPLASH-type sequence [3 voxel of the spectroscopy was calculated to cover approximately 30% of the supraspinatus muscle cross-section. When we measured the relationship between the MRS fat/water ratio and the threshold-based fat content within the central 10 × 10 × 10 mm3 region, the correlation coefficient in the central voxel was found to be 0.88 , which was comparable to the correlation coefficient measured in the entire muscle area. Finally, our patient population was not uniform across different Goutallier grades. We had few cases of Goutallier grade 0 because only symptomatic patients considering rotator cuff repair surgery were included. Our irregular patient population did not produce enough cases for individual examinations of the threshold-based fat fractions between patient subgroups of different Goutallier grades or pathologies. Correlations between threshold-based fat quantification and proton MR spectroscopy  between the fat fractions in the supraspinatus fossa and Goutallier grades, and 2) between the fat fractions in the supraspinatus muscle and MRS fat/water ratios.


In the past two decades, genetic testing for cancer risk assessment has entered mainstream clinical practice due to the availability of low-cost panels of multiple cancer-associated genes. However, the clinical value of multiple-gene panels for cancer susceptibility is not well established, especially in cases where panel testing identifies more than one pathogenic variant. The risk for specific malignancies as a result of a mutated gene is complex and likely influenced by superimposed modifier variants and/or environmental effects. Recent data suggests that the combination of multiple pathogenic variants may be fewer than reported by chance, suggesting that some mutation combinations may be detrimental. Management of patients with “incidentally” discovered mutations can be particularly challenging, especially when established guidelines call for radical procedures  in patients and families without a classic clinical history concerning for that cancer predisposition syndrome.We present two cases, one of an individual and one of a family, with multiple pathogenic mutations detected by multi-gene panel testing to highlight challenges practitioners face in counseling patients about pathogenic variants and determining preventive and therapeutic interventions.Ongoing investigation is needed to improve our understanding of inherited susceptibility to disease in general and cancer predisposition syndromes, as this information has the potential to lead to the development of more precise and patient-specific counseling and surveillance strategies. The real-world adoption of new or improved technologies into clinical practice frequently requires medical decision-making in the absence of established understanding of gene-gene interactions. In the meantime, practitioners must be prepared to apply a rationale based on currently available knowledge to clinical decision-making. Current practice is evolving to rely heavily on clinical concordance with personal and family history in making specific therapeutic decisions.The online version contains supplementary material available at 10.1186/s13053-021-00172-3. BRCA1 and BRCA2 double heterozygotes estimated the frequency of occurrence in the non-Ashkenazi Jewish population of 1:190,000 . Al. Al18]. RECQL4 is a DNA helicase gene that has been implicated in DNA double stranded break repair, nucleotide excision repair, and base excision repair, important for DNA replication and repair of UV damage [RECQL4 gene have been associated with Rothmund-Thompson (RTS), Baller-Gerold (BGS), and RAPADILINO syndromes [RECQL4 with cancer predisposition [RECQL4 mutation on cancer predisposition unknown, particularly in the context of simultaneously inherited DNA damage and repair gene mutations like BAP1 and/or MSH6.V damage –22. ThisV damage . Homozygyndromes . These syndromes . Thus, iposition . The impTable Compared to phenotype-driven single gene testing, MGPT increases the probability of identifying pathogenic mutations. Studies of large populations of women diagnosed with breast cancer suggest that nearly 8% carry a pathogenic variant that, if detected, would warrant a change in preventive care, such as secondary breast cancer screening incorporating MRI, early colonoscopy or high risk surgery . In addiAnother potential consequence of MGPT is the identification of more than one pathogenic mutation in the same individual or identification of pathogenic mutations that do not match the patient’s phenotype. Review of larger cohorts undergoing MGPT for breast, ovarian and general hereditary cancer risk has revealed that approximately 3% of individuals test positive for pathogenic mutations in multiple genes . This caIdentifying patients with multiple clinically actionable mutations has important implications for patients and their family members, yet much remains unclear regarding the consequence of carrying more than one pathogenic mutation. Our understanding of how combinations of mutations may interact to alter the ultimate profile of cancers in a patient, or their family, is currently very limited –34. CertOGG1 glycosidase gene of the base excision repair pathway has been shown to increase the penetrance of ovarian cancer in patients with BRCA1/2 mutations [OGG1, thus contributing to further genomic instability via DNA damage and telomere shortening [cyclin-dependent kinase inhibitor (CDKN2A) gene and variants of the melanocortin-1 receptor (MC1R) gene that have previously been associated with red hair, fair skin and sensitivity to ultraviolet light  have been found to significantly increase melanoma penetrance and decreased the age of onset by 20 years compared to individuals carrying the CDKN2A mutation alone [Detrimental consequence: Some germline cancer susceptibility mutations may interact in an additive or synergistic manner to increase the penetrance of cancers related to other germline cancer susceptibility mutations. There is some precedence for this in the literature. The rs2304277 variant in the utations . The mutortening . In addion alone . Earlieron alone .MSH6, have been clearly associated with a high risk of cancer development [Beneficial consequence: Increased fragility of cells carrying multiple mutations could counterintuitively result in an overall cancer risk that is less than the sum of the individual risks from the inherited germline mutations. There may be a restricted profile of tertiary and subsequent mutations that a cell can handle. This may lead to increased apoptosis, cell death or senescence as somatic mutations accumulate, which could reduce penetrance or improve prognosis of tumors. For example, as outlined above, germline mutations affecting DNA repair genes, such as elopment . Howeverelopment . These felopment .Genomic Background and Environmental Exposure: In addition to the consequence that inherited germline mutations may have on each other, the overall penetrance of a cancer predisposition syndrome is also affected by the individuals genomic background and environmental exposures, such as ultraviolet radiation. For example, protective modifier genes may exist that mitigate the risks conferred by high-penetrance genes. A recent analysis of 589,306 genomes by Friend et al. identified 8 individuals resilient to severe Mendelian childhood diseases . These iBased on this framework and the limited data we have available; a few effects are possible:Various combinations of germline cancer susceptibility mutations most likely interact in unique ways. Some combinations may potentiate risk for specific malignancies while others may attenuate risk, perhaps depending on specific pathway interactions. This is likely to create difficulty in ascribing a particular cancer syndrome to a family or individual. As genetic testing becomes more widely available and used, it will be critical to expand our knowledge of the interactions among germline mutations and the ultimate genotype-phenotype consequences.As costs of MGPT decrease, the risk of missing pathogenic mutations may outweigh the arguments against panel testing. MGPT offers lower cost of testing per gene . HoweverWhile our understanding of cancer heritability, and particularly the interplay among multiple pathogenic mutations, remains unclear, it is important to acknowledge and accept the uncertainty while striving to advance the field toward a more comprehensive understanding. Prior to initiating testing, it is important to ensure that both the counselor and the patient are comfortable with results of unknown significance . IdeallyWhile our understanding of the interplay among combinations of germline cancer susceptibility gene mutations remains incomplete, we need to be prepared to provide counseling and screening recommendations to the best of our abilities. Available screening guidelines for each relevant mutation should be reviewed Table , howeverManagement of patients with “incidentally” discovered mutations can be particularly challenging, especially when established guidelines call for radical procedures  in patients and families without a classic clinical history concerning for that cancer predisposition syndrome. For this reason, current practice is evolving to rely on clinical concordance with personal and family history in making specific screening or therapeutic decisions. In the case that genetic test results reveal a pathogenic or likely pathogenic mutation in an individual without a personal or family history suggestive of that particular cancer pre-disposition syndrome, less rigid screening protocols could be considered. For example, if a patient tests positive for a pathogenic mutation in MSH6 but does not have a personal or family history suggestive of classic Lynch Syndrome, delay of initial colonoscopy to age 25–30 or less frequent colonoscopies could be considered. Cascade testing may also be discouraged in extended family.In the case that an individual has a family history of cancers that lie outside of the established spectrum of cancer predisposition identified by germline mutations, the 10-year rule may be utilized. Screening for that particular malignancy may be instituted when the individual is 10 years younger than the earliest known diagnosis in the family. This 10-year rule may be applied to first- and second-degree relatives.MSH6, and confirmed a germline mutation in MSH6, while revealing additional mutations in BAP1 and RECQL4 genes (Table BAP1 or RECQL4 mutations prior to testing.MGPT was performed after her colon cancer had negative IHC staining for BAP1), ophthalmology every 6 months for dilated fundus examination and annually for ultrasound biomicroscopy (UBM) . She also undergoes annual renal ultrasound, and MRI chest and abdomen every 2 years  [BAP1 and RECQL4 mutations. No specific screening for osteosarcoma is performed.Her screening regimen consists of a combination of the recommendations for BAP1 Tumor Predisposition Syndrome and Lynch Syndrome, respectively. She is seen by dermatology every 6 months for full body skin examination  . She conMSH6 and BAP1 (Table . One sister (IV-3) did not inherit either mutation; one (IV-4) inherited just the MSH6 mutation, one  inherited just the BAP1 mutation, and one (IV-6) inherited both MSH6 and BAP1 mutations.The sisters in Family 2 demonstrate a Mendelian inheritance pattern of the two familial cancer predisposition mutations in MSH6 and BAP1 . One sister (IV-3) did not inherit either mutation; one (IV-4) inherited just the MSH6 mutation (index case for Family 1), one  inherited just the BAP1 mutation, and one (IV-6) inherited both MSH6 and BAP1 mutations.The arrow indicates Patient 2, the proband for Family 1. The sisters in generation IV of Family 2 demonstrate a Mendelian inheritance pattern of the two familial cancer predisposition mutations in BAP1 c.38-1G > A likely pathogenic variant and site-specific testing for the familial MSH6 mutation was negative. She is screened with full body skin examinations every 6 months, dilated fundus examinations every 6 months with annual UBM, annual renal ultrasound and MRI chest and abdomen every 2 years.Our patient was found to have a MSH6 suggested a high probability of Lynch syndrome, in the absence of a previous family history of colorectal cancer. Ambry Genetics panel testing revealed an MSH6 EX3-9del. She subsequently underwent a prophylactic total abdominal hysterectomy with bilateral salpingo-oophorectomy (TAHBSO), which revealed a Stage IA, grade 1 endometrial cancer at 54. At 55, she was diagnosed with a Stage 1B ER/PR-negative left-sided breast cancer, following routine mammography. Immunohistochemical studies performed on the breast biopsy tissue demonstrated intact expression of DNA mismatch repair proteins MLH1, MSH2, MSH6 and PMS2, suggesting that her breast cancer was sporadic and not associated with microsatellite instability.The index case (IV-4) had a history of a tubular adenoma in the hepatic flexure, several small adenomas, a hyperplastic polyp, and two tubular adenomas in the ascending colon and sigmoid colon at age 51; then a tubular adenoma in the sigmoid colon and a right hepatic mass with no definitive invasive carcinoma at 54. She underwent a prophylactic right hemicolectomy a month later that revealed a 2.6-cm moderately differentiated mucinous adenocarcinoma, with invasion through the muscularis propria and superficially into subserosa adipose tissue (Stage 2). Loss of nuclear expression of The youngest sister (IV-6) was found to have both familial mutations after testing for a broad profile  tested negative for both familial mutations through site-specific testing for the familial variants through Ambry Genetics.Cancer genetics is advancing quickly as a tool for precision medicine as we move into an era of whole-exome and whole-genome sequencing. With large panel testing becoming more widely available and affordable, the challenge of counseling and managing patients with mutations in multiple germline cancer susceptibility genes, with incompletely understood interactions, will become more prevalent. To address our questions and uncertainties, we must be prepared to track, research and share our insights into the human genome. As we work to advance the field toward a more comprehensive understanding of predictive cancer genetics and the complex interplay of other genomic and environmental exposure effects, it is important that we work to individualize care for each patient while recommending a rational plan based on existing data.We support broad MGPT in assessing patients and families for inherited predisposition to cancer and other diseases. The practice of clinical genetics is in a period of rapidly advancing understanding of genotype-phenotype correlations. While this raises puzzling and challenging questions, only through more detailed, open-ended testing and meticulous data collection will we better tease apart the complex results. Ironically, this conundrum highlights the continued relevance and importance of family history as a practical guide, despite the immense and improving technology at our disposal.Additional file 1. Invitae Multi-Cancer Panel. Broad Profile Testing for Patient 2’s youngest sister (IV-6).


Wheat cultivars ‘TAM 111’ and ‘TAM 112’ have been dominantly grown in the Southern U.S. Great Plains for many years due to their high yield and drought tolerance. To identify the molecular basis and genetic control of drought tolerance in these two landmark cultivars, RNA-seq analysis was conducted to compare gene expression difference in flag leaves under fully irrigated (wet) and water deficient (dry) conditions. A total of 2254 genes showed significantly altered expression patterns under dry and wet conditions in the two cultivars. TAM 111 had 593 and 1532 dry–wet differentially expressed genes (DEGs), and TAM 112 had 777 and 1670 at heading and grain-filling stages, respectively. The two cultivars have 1214 (53.9%) dry–wet DEGs in common, which agreed with their excellent adaption to drought, but 438 and 602 dry–wet DEGs were respectively shown only in TAM 111 and TAM 112 suggested that each has a specific mechanism to cope with drought. Annotations of all 2254 genes showed 1855 have functions related to biosynthesis, stress responses, defense responses, transcription factors and cellular components related to ion or protein transportation and signal transduction. Comparing hierarchical structure of biological processes, molecule functions and cellular components revealed the significant regulation differences between TAM 111 and TAM 112, particularly for genes of phosphorylation and adenyl ribonucleotide binding, and proteins located in nucleus and plasma membrane. TAM 112 showed more active than TAM 111 in response to drought and carried more specific genes with most of them were up-regulated in responses to stresses of water deprivation, heat and oxidative, ABA-induced signal pathway and transcription regulation. In addition, 258 genes encoding predicted uncharacterized proteins and 141 unannotated genes with no similar sequences identified in the databases may represent novel genes related to drought response in TAM 111 or TAM 112. This research thus revealed different drought-tolerance mechanisms in TAM 111 and TAM 112 and identified useful drought tolerance genes for wheat adaption. Data of gene sequence and expression regulation from this study also provided useful information of annotating novel genes associated with drought tolerance in the wheat genome. Triticum aestivum L.) productivity worldwide particularly under modeled global climate change scenarios. It is estimated that almost 50% of wheat cultivated in the developing world is sown under dryland cropping systems1. Increasing resilience to abiotic stresses through genetic improvement thus become a critical component of wheat breeding. To identify genes related to drought tolerance and understand mechanisms of plant reaction to water deficit in this type of germplasm is crucial for developing cultivars with better water use efficiency.Drought (water deficit stress) is a major environmental stress threatening wheat . The two cultivars are also used in crossing blocks of U.S and global breeding programs for improving drought tolerance. Reddy et al.18 used microarray analysis to compare gene expression in TAM 111 and TAM 112 under water deficit stress and fully irrigated condition, and identified 1657 transcripts commonly existing in both cultivars that showed expression difference under the two conditions with transcripts mostly related to photosynthesis, carbohydrate metabolism, phytohormone metabolism, and other dehydration responses. However, the microarray used only a subset of genes and thus limited ability of detecting drought-response genes beyond the set. In addition, Xue et al.19 indicated that TAM 111 and TAM 112 showed different water-use efficiency and stem dry weight at anthesis for response to drought, indicating the two cultivars might have different mechanisms of drought tolerance. Therefore, identifying and comparing the genome-wide response to water deficit stress between TAM 111 and TAM 112 will uncover drought tolerance mechanisms, and aid the breeding processes by determining the key pathways.The Southern Great Plains (SGP) of the U.S. include the major winter wheat growing areas in Nebraska, Kansas, Oklahoma and Texas, and has a semi-arid climate with annual precipitation averaging about 480 mm and wheat growing season precipitation around 250 mm20 and reveal the precise location of transcription boundaries as well as sequence variations21. Recently, RNA-Seq has been successfully utilized in wheat for analyzing expression of genes response for heat stress22, salt stress24, drought26 and flowering regulation27. Particularly, with the availability of whole genome sequences in wheat landrace ‘Chinese Spring’28 and pan-genome sequences (www.10wheatgenomes.com) from ten wheat cultivars, physical positions of genes identified through RNA-seq can be easily determined. Therefore, using RNA-Seq analysis can not only detect differentially expressed genes (DEGs) as candidate genes for the target traits, but also verify genes/QTLs identified through genetic linkage and association analysis according to corresponding genomic positions. Additionally, gene sequence from RNA-Seq can be used to develop genic markers for marker-assisted selection and genomic selection in drought tolerance breeding29.By using high-throughput sequencing technologies, RNA-Seq can quantify gene expression levels with high accuracy in the entire transcriptomeThis research aims to identify drought responsive genes in TAM 111 and TAM 112. The two cultivars were grown in a greenhouse under fully irrigated (wet) and drought (dry) conditions, and flag leaves from main tillers of the two cultivars were collected at heading and grain filling stages for RNA-seq studies. By comparing differentially expressed genes (DEGs) between the two cultivars under the irrigated and drought conditions, we identified the gene regulatory networks that are common between the two cultivars, as well as those specific to each.17. TAM 111 has the pedigree ‘TAM 107’//TX78V3620/CTK78/3/ TX87V1233, and TAM 107 has the pedigree ‘TAM 105’*4/’Amigo’. It had higher grain yield in irrigated conditions but lower grain yield under extended drought conditions than that of TAM 112. TAM 112 was derived from the cross U1254-7-9-2-1/TXGH10440 where the male parent was a TAM 110 sib (has pedigree ‘TAM 105’*4/’Amigo’)*5//’Largo) and TAM 107 sib was in the recurrent parent30. TAM 200 (has pedigree 391-56-D8/’Tascosa’//’Centurk’) *3/’Amigo’) was in the pedigree of the female parent U1254-7-9-217.Therefore, the two cultivars are related with partially shared pedigree about less than 40% in common. TAM 112 is 2–3 days earlier on heading and maturity than TAM 111 but with similar height because both have Rht1. TAM 112 has 1AL.1RS, Gb3 for greenbug resistance to biotype E, and CmcTAM112 for resistance to wheat curl mite and is the most drought tolerant winter wheat in the US Great Plains33.The two hard red winter bread wheat cultivars, TAM 111 and TAM 112, have excellent drought tolerance and were developed by Texas A&M AgriLife Research18. Briefly, a randomized complete block design (RCBD) was used with the sampling time  as blocks. Three replicates were included in each block, and four pots within each replicate were used for each treatment with one pot containing three plants of one cultivar, which resulted in the total of 16 pots (48 plants) per replication and 48 pots (144 plants) in each block. The pots were maintained at 100% gravimetric water content (GWC) for the first seven weeks. Water deficit treatments were started at the jointing stage (50 days after transplanting) with GWC reduced to around 50% for the dry treatment but maintained at 90% for the wet treatment.The water deficit treatments and sample collection were as described in Reddy et al.34. Wheat flag leaf can contribute as high as 45–58% of photosynthetic performance under favorable conditions35 with 41–43% of assimilates used in grain filling after flowering36. Therefore, flag leaf tissues from primary tillers of four individual plants in each replicate were collected and pooled as one sample at each stage of heading (HD) (79 days after transplanting) and middle grain filling (GF) . Leaf samples were immediately put into liquid nitrogen after their harvest and then stored at − 80 °C for processing. RNA was extracted using a Qiagen-RNeasy Mini kit according to instruction provided by the manufacturer. For preparing sequencing libraries, the TruSeq RNA Sample Preparation kit v2 was used following the manufacturer’s instructions. Briefly, mRNA was purified by using poly-T oligo-attached magnetic beads, cDNA was then synthesized after fragmentation, followed by A-tailing, adaptors ligation and PCR amplification. After quality check, each library was then deeply sequenced on a single lane of Illumina HiSeq 2000 to generate 75 bp pair-end reads.Wheat flag leaves are the main organs for implementing photosynthesis and providing the major assimilate source for plant growth, spike development and sensing environmental signals for adaptation37. Raw reads were filtered by removing adapters and trimming low quality bases (Phred score < 20) at the end of reads using Trimmomatic v0.3838. The wheat genome RefSeq v1.0 assembly and gene model annotation files were downloaded from the International Wheat Genome Sequencing Consortium (IWGSC)28 (https://urgi.versailles.inra.fr/download/iwgsc/IWGSC_RefSeq_Assemblies/v1.0/). The filtered reads were then aligned to the reference genome using tool TopHat239. Transcript assembles were generated using the computer package Cufflinks37, and all assembled transcripts were further merged through the tool Cuffmerge using the wheat reference gene annotation as a guide. The tool Cuffdiff that was included in the Cufflinks package was then used to calculate gene expression level and normalize transcripts abundance to FPKM value (Fragment per kilobase of transcript per million reads mapped) and then make calls of differentially expressed genes (DEGs). The significance  of DEGs were adjusted using the Benjamini and Hochberg multiple test correction approach40 to control the false discovery rate (FDR), and only the genes with an adjusted P value < 0.05 (FDR < 0.05) and had a fold change value greater than two  were considered to have significant expression difference. In this research, the gene expression comparison was performed separately between two treatments (dry vs. wet) and between two cultivars (TAM 111 vs. TAM 112). In addition, the gene expression regulation was considered as up-regulated if the expression level is higher under the dry conditions (Log2[fold change] > 0), and down-regulated if the expression level is lower under drought treatment (Log2[fold change] < 0).Transcriptome and gene expression analysis were conducted using computer program Cufflinks according to Trapnell42 was used for functional annotation of the genes with significantly different expression levels under dry and wet conditions. The tool NCBI BLAST was used to compare DNA sequence of each DEGs with those stored in NCBI GenBank database (https://www.ncbi.nlm.nih.gov/) to infer gene function with BLAST expectation value  threshold set at 1.0 × 10–5, and the tool InterProscan using the inferred protein sequences (motifs) to search against InterPro databases with the web service provided by EMBL-EBI (https://www.ebi.ac.uk/interpro/), to find gene ortholog (GO) related information. The tool GO Mapping was used to retrieve GO terms associated with BLAST search hits from NCBI GO database and online protein databases . The tool Gene Ontology Annotation was then used to assign GO terms to gene sequences, and tool Gene Ontology Graphs was used to develop hierarchical structure of the gene ontology according to biological processes, protein molecule functions and subcellular localization of the proteins. For genes with ambiguous function descriptions from Blast2Go annotation, gene sequences were manually searched against NCBI43, and the translated protein sequences were used to search against online protein databases again to infer their function.The computer program Blast2Go42, and the graphs of each cultivar were used to find the difference between TAM 111 and TAM 112 for their drought response. In addition, expression comparison of genes in the process of responding to water deficit stress, other drought related processes of heat and oxidative stress response, abscisic acid (ABA)-activated signal pathway and transcription regulations were also performed in the two cultivars to determine their specificity in drought tolerance.To understand drought tolerance mechanisms in TAM 111 and TAM 112, comparison of gene expression difference between dry and wet conditions in each cultivar and expression difference between them under dry or wet conditions were separately conducted. DEGs common in both cultivars thus represented the similar mechanisms they shared for response to drought, and DEGs specific to each cultivar or showing different regulation patterns between them were the indication of unique drought-tolerance mechanism in each. The annotated genes response to drought were then used to develop hierarchical diagrams according to their roles in biological processes, molecule functions and cellular component locations through Blast2Gohttps://bioinfo.ut.ee/primer3/) and then BLAST search against wheat reference genomic sequence (https://wheat-urgi.versailles.inra.fr/Seq-Repository/BLAST) to check specificity of the primers. Expressions of four genes were determined using Comparative Quantification and (ΔΔCt) method using Actin gene as an endogenous control. PCR amplification was conducted in a 20 µl mix contained 20 ng of cDNA template, 1 × SYBR Select Master Mix (Applied Biosystem), and 0.3 µM each of forward and reverse primers. Thermal cycling conditions were set at 50 °C for 2 min, 95 °C for 10 min, followed by 40 cycles of denaturing at 95 °C for 15 s and annealing at 60 °C for 1 min, with fluorescence detection at the end of each cycle. The amplification of a single product per reaction was confirmed by melting curve analysis. The primers sequences of four genes and the endogenous control (Actin gene) were listed in Table To confirm the RNA-seq results, the expression levels of four differentially expressed genes (two were up-regulated and two were down-regulated) were analyzed through real-time quantitative polymerase chain reaction (RT-qPCR) using an Applied Biosystems ViiA 7 Real-Time PCR System. Reverse transcription was performed using Qiagen’s Omniscript RT Kit (Cat. # 205113) via standard protocol described by manufacturer. Primers of four genes were designed using Primer 3 web version 4.1.0  being common in both cultivars, and 438 (19.4%) and 602 (26.7%) specific to TAM 111 and TAM 112, respectively  sequence database, all of them had high similarity to the corresponding sequences  annotation and NCBI BLAST against the online DNA and protein databases inferred the potential function of 1855 genes whereas function of 399 genes remained unknown. The 399 genes with unknown functions included 258 encoded either predicted or uncharacterized proteins and 141 had no BLAST hits (no similar DNA sequence) in NCBI DNA database and no similar GO terms can be determined according to current protein databases. However, using those 141 genes with no BLAST hits as queries to BLAST against IWGSCes Table , suggestAccording to 1855 genes with assigned functions, two sets of genes with significant dry–wet expression difference in TAM 111 1389 genes) and TAM 112 (1549 genes) were used to develop hierarchical graphs in each cultivar according to their roles in biological processes, molecule functions and locations in cellular components. The hierarchical biological processes diagram included 1153 genes with 884 and 978 differentially expressed in TAM 111 and TAM 112, respectively  and two down regulated (L_054218 and L_074394) were selected for validating the expression level changes in dry and wet condition indicated through RNA-seq analysis. RT-qPCR using Actin gene as an endogenous control revealed similar gene expression fold change under different condition at heading and grain filling stages in both cultivars (Fig. 45 estimated that the variability of 40% annual wheat productivity was mainly due to drought and heat stresses in the majority of wheat production regions. However, wheat tolerance to drought is a very complex trait regulated at different levels of gene expression, cellular response and physiological reaction with numerous minor effect genes involved46. Using transcriptomic analysis such as micro-array and RNA-seq to compare gene expression under drought and irrigated conditions provided a quick way of identifying genes related to drought response. Particularly, as DNA sequences of wheat whole genome are available now, RNA-seq can accurately identify genes and compare their expression levels under different conditions. In this study, we used RNA-seq and identified 2254 genes that are differentially expressed in cultivars TAM 111 and TAM 112 under dry and wet conditions at heading and grain filling stages, and RT-qPCR was used to validate expression of four DEGs in this study and five DEGs in Reddy et al.18. According to gene annotation through online DNA and protein databases, those differentially expressed genes were encoding key enzymes, transcription factors, signal receptors and cellular components that were involved in different biological processes and pathways for responding to abiotic stresses as well as defense responses. Particularly, genes identified in this study involved in pathways such as flavonoid biosynthesis, fructan biosynthesis in starch and sucrose metabolism and enzymes that having protein disulfide oxidoreductase activity and maintain cell redox homeostasis have already been reported to associate with drought tolerance in wheat47. Also, the subcellular locations of DEGs encoded proteins in peroxisome, nucleus and mitochondria associated with drought stress response were reported in many crops50. Therefore, drought response in TAM 111 and TAM 112 would have similar processes that drought signals promote plants to maintain water homeostasis and redox homeostasis to prevent acute cellular damage and membrane integrity53.Drought stress at heading and grain filling stages of wheat can cause great reduction in grain yield, lower kernel weight and deteriorate end-use quality. Zampieri et al.18 and Zupin et al.54, and DEGs encoding heat shock protein, oxidoreductase, late embryogenesis abundant protein and dehydrin were mainly up-regulated in two cultivars under drought is in consistent with that increasing level of those proteins can maintain cellular redox homeostasis particularly at grain filling stage62. Expression of genes for transcription factor and proteins involved in ABA-induced signal pathway were either up- or down-regulated in both cultivars but were more up-regulated in TAM 112, which was in accordance with that ABA mostly plays the central role of regulating expression of genes for plant response to stress65, but different regulation in some genes between two cultivars indicated different strategies may be used for drought tolerance.In this research, the differentially expressed genes encode aquaporin were all down-regulated for cellular osmotic adjustment to prevent water loss, which agreed with results from Reddy et al.19. From the same experiment, TAM 111 showed significant higher kernels per spike but TAM 112 showed significant higher thousand kernel weight than those of TAM 105 in both dryland and irrigated conditions. This is also consistent with what was found from more than 10 dryland and irrigated environments, TAM 112 had higher values of spikes per square meter, hardness and flour protein while TAM 111 had higher values of kernels per spike, single head grain weight, seed diameter and flour yield67. According to few studies about physiological and molecular basis of drought tolerance in the two cultivars, both had higher ABA content under drier conditions; however, TAM 112 had a higher ABA content and more robust expressions of genes involved in ABA-signal pathway compared to TAM 111 under dry condition18. Thapaet al.69 reported TAM 112 showed better water use efficiency than TAM 111 and thus had better tolerance under continuous drought conditions. Field yield trials also indicated that TAM 112 performed relatively better under sustained drought. In this research, out of 2254 dry–wet DEGs identified from the two cultivars, 1214 were common in both cultivars and 438 and 602 were present only in TAM 111 and TAM 112, respectively. Over 50% of dry–wet DEGs found in both cultivars supported that the two cultivars have robust drought tolerance derived from conserved regulatory network, whereas DEGs were found to be specific in each cultivar indicating that they have specific mechanisms against drought. Based on the hierarchical structure of biological processes, molecule functions and cellular components developed using genes with known functions, though two cultivars shared a large portion of dry–wet DEGs for each process, TAM 112 had more genes than TAM 111 that were up-regulated under drought. For processes such as protein phosphorylation, TAM 111 had more genes differentially expressed than TAM 112, but their expressions were mostly decreased under drought. Similar observations were found for genes with function of adenyl ribonucleotide binding or those with encoded proteins located in nucleus and plasma membrane with functions of regulating transcription and transmembrane transporting, which indicated that TAM 112 had relatively more active gene expression regulations than TAM 111 under drought.Winter wheat cultivars TAM 111 and TAM 112 were widely adapted to the Southern Great Plains and have excellent drought tolerance. Both TAM 111 and TAM 112 had 19.1% and 19.3% higher grain yield in dryland and 8.1% and 7.2% higher in irrigated field comparing with the grain yield of TAM 105-2, lower stomatal conductance and gas exchange parameters, and higher photosynthetic water use efficiency under water deficit stress, and this was manifested in higher yield under drought68. On the other hand, higher yield of TAM 111 under drought was more associated with high spike and stem dry weight at anthesis and maturity19. In addition, TAM 111 tends to have more sterile spikelets per spike under water deficit stress compared to TAM112 although no significant difference was observed in their primary spikes18. Grain abortion and reduce plant cycle length were commonly known as strategies of plants response to long-term drought51. Therefore, the large portion of drought response genes shared by TAM 111 and TAM 112 contributed to their good drought tolerance. However, active expression of specific dry–wet DEGs in TAM 112 increased its resilience to and had higher grain yield under the sustained drought, whereas decreased expression of specific DEGs under drought may save more energy in TAM 111 for transporting carbohydrates from stems and spikes to seeds or even adjust gene expression to cause seed abortion in some spikelets to maintain grain production under drought.Based on expression comparison for genes involved in responding to water deficit stress, heat stress, oxidative stress, ABA-activated signal pathway and transcription factors, TAM 112 always had a greater number of dry–wet DEGs than TAM 111 with significantly increased expression under dry conditions. This further suggests that active gene expression in TAM 112 support its better water use efficiency during drought periods, whereas TAM 111, though with most of dry–wet DEGs shared with TAM 112, had a greater number of down-regulated genes, potentially to protect it from drought and maintain its growth. Both greenhouse and field studies showed that TAM 112 had more tillers per spike and spikes mAdditionally, 399 genes showed differential expression in TAM 111 and TAM 112 have not been functionally annotated, which included 258 encoding predicted but uncharacterized proteins and 141 with no BLAST hits. Expression analysis of those genes in this research indicated they were related to drought stress responses. Since TAM 111 and TAM 112 are cultivars with unique drought tolerance mechanisms, those genes with unknown functions may be novel. Further research is necessary to reveal the protein products and functions of those genes.46, utilization of those genes/QTLs is challenging due to their small effects and instability caused by strong genetic × environment interaction70. Drought tolerance is a complex trait involving numerous genes involved in many biological processes, and selections of a few drought response genes with minor effects is most unlikely to confer a significant improvement on drought tolerance across diverse cultivars and environments44. Genomic selection of accumulating beneficial alleles at the whole genome level may provide a promising strategy for rapid and effective genetic gain on drought tolerance breeding44. Through RNA-seq, the sequences of the differentially expressed genes under drought conditions can be used to develop genic markers target to all drought response genes, and these markers can be combined with other markers covering the whole genome to conduct genomic selection toward drought tolerance improvement. The dry–wet DEGs identified in TAM 111 and TAM 112 from this research can be used to develop markers for efficiently utilizing the alleles of TAM 111 and TAM 112 for enhancing drought tolerance.Although many putative genes and QTLs conferring drought tolerance in wheat have been identified12 of wheat thus need to be investigated. This research identified few genes related to root development though only flag leave tissue was used for expression analysis. In addition, gene expression for drought response at other stages such as stem elongation and early reproductive periods also plays important roles on grain yield26. Future research at other growth stages or utilizing root tissue to compare gene expression under dry–wet conditions will enrich our knowledge of drought tolerance mechanisms in wheat.Lastly, this research used only flag leaf tissue for gene expression comparison at heading and grain filling stages, but root system of wheat plays very important roles for water intake from soil and affects water use efficiency. Comparing the expression of genes controlling root system architecture including root density, root length and root distributionSupplementary Information


RB1) plays a critical role in coordinating multiple pathways that impact cancer initiation, disease progression, and therapeutic responses. Here we probed molecular features associated with the RB-pathway across 31 tumor-types. While the RB-pathway has been purported to exhibit multiple mutually exclusive genetic events, only RB1 alteration is mutually exclusive with deregulation of CDK4/6 activity. An ER+ breast cancer model with targeted RB1 deletion was used to identify signatures of CDK4/6 activity and RB-dependency (CDK4/6-RB integrated signature). This signature was prognostic in tumor-types with gene expression features indicative of slower growth. Single copy loss on chromosome 13q encompassing the RB1 locus is prevalent in many cancers, yielding reduced expression of multiple genes in cis, and is inversely related to the CDK4/6-RB integrated signature supporting a cause-effect relationship. Genes that are positively and inversely correlated with the CDK4/6-RB integrated signature define new tumor-specific pathways associated with RB-pathway activity.The retinoblastoma tumor suppressor gene ( Erik Knudsen et al. present a pan-cancer analysis of the RB tumor suppressor protein pathway in 31 tumor types. They find that pathway deregulation is multi-faceted with context dependent association with survival. However, gene expression features are surprisingly invariant and support new therapeutic targets. RB1 tumor suppressor was identified based on bi-allelic inactivation in retinoblastoma3. However, it has become clear that dysregulation of the RB protein pathway is a veritable hallmark of the cancer state. The RB-pathway is canonically described by oncogenes CDK4, CDK6, and CCND1 and the tumor suppressors RB1 and CDKN2A4. In this context, it has been proposed that these lesions are mutually exclusive and thus serve to define a simple linear pathway6. This network integrates mitogenic and oncogenic signaling pathways and plays critical roles in the etiology, progression, and therapeutic response in multiple different cancers7.The 10. The activity of these kinase complexes are kept in check by endogenous CDK4/6 inhibitors  that limit inappropriate proliferation due to oncogenic signaling12. The principle target of this signaling network is the RB protein and related proteins encoded by the RBL1 and RBL2 genes14. The RB protein can function to repress a large transcriptional program of genes that are required for progression through S-phase, mitosis, and cytokinesis17. When dephosphorylated or hypophosphorylated RB is active in transcriptional repression; however, CDK4/6-mediated phosphorylation initiates the inactivation of RB and enables the expression of downstream genes that drive progression through the cell cycle and cell division19. Although much attention has been focused on cell cycle control mediated by RB, it is clear that RB-pathway impacts tumor metabolism, immunological features of the tumor microenvironment, and complex epigenetic states, often in a context-dependent fashion21. How the RB-pathway controls these context dependent features across human tumors remains poorly understood.Physiologically CDK4 and CDK6 activity is positively regulated by D-type cyclins that are responsive to proliferative signals that drive cell cycle progressionRB1 was the first tumor suppressor gene identified, there are a large number of questions that remain relative to biological functions that could promote targeted therapeutic strategies for the treatment of cancer21. At present, the therapeutic focus has been on leveraging CDK4/6 inhibition to activate RB and limit proliferation of tumor cells to delay disease progression10. In spite of success in ER+ breast cancer24, this approach has not been as successful as anticipated across the large number of different tumor types where it has been tried. These clinical challenges suggest that an improved understanding of the circuitry involving the RB-pathway could be useful in either improving the utility of CDK4/6 inhibitors or advancing new approaches to target RB-pathway perturbation 25. For example, recent studies have suggested that the deregulation of cell cycle transitions upon RB1 loss can represent a specific dependency on aurora kinases that can be targeted therapeutically27. In contrast to therapeutic exploitation of rapidly proliferating cancer cells, slow growing or dormant tumor cell populations can represent particular challenges since they are resistant to such therapies yet can seed recurrence and resistance to chemotherapy28. Therefore understanding how to eradicate biologically distinct forms of cancer is of clear significance.While RB1 impact clinical outcomes, and has defined unique interactions that could represent new vulnerabilities for the treatment of cancer.Interrogating a large collection of molecular data from diverse tumor-types would be hypothesized to drive a clearer understanding of both the canonical features of RB-pathway cell cycle control as well as non-canonical, context dependent functions that may be leveraged for therapy. To this end, a pan-cancer molecular analysis of the RB-pathway was employed to probe genetic features across tumor types and gene expression relationships. This analysis sheds new light on genetic/gene expression interactions, how cell cycle regulatory networks related to RB1, RBL2, and RBL1) are also observed in specific tumor settings . Surprisingly, and contrary to expectation, the genetic amplification of CDK4 and CCND1 are not mutually exclusive and appear to be co-occurring suggesting that these events coordinately contribute to disease , suggesting that the control of CDK4/6 activity and RB-status appear to define a single element of the pathway  or tumors where the RB-pathway is inactivated in veritably all tumors by the presence of HPV  that yields RB inactivation via the E7 viral oncoprotein29    Fig. . InteresRB1 function can clearly be compromised by multiple events in addition to direct genetic loss in human cancers , we focused on developing a transcriptional tool to evaluate RB activity based on transcription that could be broadly deployed across tumors. To develop the “seed” for this signature, the ER+ breast cancer cell line MCF7 was treated with the CDK4/6 inhibitor palbociclib to mimic the action of CDKN2A and induction of RB activity , and 36% of heterozygous tumor types  were selected for analysis  we utilized the CDK4/6-RB integrated signature to define genes that are positively and inversely correlated with deregulated pathway function. Bootstrapping was utilized to define significantly correlated genes in each tumor type  defined relatively consistent enrichment for cell cycle nodes that are positively correlated as expected; however, there were a wide diversity of processes  that were inversely correlated . These data and the reciprocal relationship between RB1 and CDKN2A expression strongly support the contention that RB1 loss universally obviates the evolutionary advantage imparted by CDK4/6 deregulation. These data underscore the concept that RB-status should be generally considered as an exclusion criteria in the use of pharmaceutical agents that target CDK4/6 activity34.The core RB-pathway understanding was built on mutual exclusive relationships that were observed in cell lines and surprisingly limited tumor analysisRB1, there is frequent single copy loss along 13q in many tumor types. The structural changes and relationship to RB1 deletion suggest different evolutionary forces at play in different tumors. In tumors such as prostate, bladder, and sarcoma the single copy loss is focused over the RB1 locus with deletion occurring at reasonably high levels. Ostensibly these data reflect positive-selection associated with RB1 loss and is consistent with the finding that RB1 loss occurs more frequently in metastatic advanced cancers of this type  and is associated with poor outcome35. Surprisingly, there are other tumor types where there is essentially no selection for deletion of RB1 for example in kidney cancers or cervical cancer, even though there is substantial single copy loss. In the case of cervical cancer it is clear there is no evolutionary pressure to lose RB1 due to HPV36. Why RB1 loss does not occur in other cancers  is less clear, however, since there is co-occurrence with deregulation of CDK4/6 activity the selective pressure may be limited. Similarly, since one copy loss appears to deregulate features of cell cycle perhaps there is little/no selective pressure to complete gene deletion. The functional analysis of single copy loss of RB1 is very limited, although studies do suggest the loss of a single copy of RB1 is sufficient to contribute to disease relevant phenotypes in mouse and human tumor models38.The evolutionary track of cancers can be inferred via the genetic features of tumor suppressor loss. In the context of 40. Multiple gene expression signatures related to this pathway have been developed in different settings and models45. These signatures are well conserved and related to RB-dependent transcriptional repression across a host of tumor types. The CDK4/6-RB integrated signature developed herein behaves in a highly consistent fashion across all tumor types analyzed, suggesting that this gene expression module is essentially invariant. While this signature can have prognostic value, it is largely limited to those tumor types that have relatively low average signature value which would be inclusive of more indolent tumor types . However, the signature has prognostic activity in tumors that are highly lethal , albeit with lower proliferative indexes. The functional relationship between gene expression signatures linked to RB activity and actual RB1 loss in cancer has been limited with disparate conclusions46. However, the vast majority of consistently repressed genes with RB1 loss are downregulated in cis, both with single copy loss and RB1 deletion. Those genes that are upregulated are largely related to cell cycle control/E2F activity and are coincident with the CDK4/6-RB integrated signature. These findings reinforce the concept that genetic aberrations targeting RB1 do, in fact, drive deregulation of functionally derived signatures which are broadly manifest in cancer. Presumably, in tumor types such as LAML or COAD there are pathway features distinct from RB loss that are driving the differential expression of these genes.It is well known that a key feature downstream of the CDK4/6-RB pathway is transcriptional pathway coordinated by E2F and other transcriptional regulatorsRB1 deficient tumor models27. However, these data also illustrate that these same tumors are preferentially engaged in translation, splicing, proteasome function, and other cellular functions that are likely critical for facilitating rapid cell division . Therefore, these tumors could be selectively sensitive to agents that target these processes . This concept has been tested in limited contexts evaluating either genetic interactions 47 or drug sensitivities specific to RB-deficient tumors48. Conversely, we identify a host of processes that would appear to be more engaged in indolent tumors or those that have forced out of the cell cycle therapeutically. This includes genes involved in immunological responses that have been functionally associated with response to immune checkpoint inhibition in tumor models exposed to CDK4/6 inhibitors49. Whether other processes  could be selectively targeted in such tumor cell populations will need to be determined given the profound alterations in genes associated with these processes. However, there is evidence that dormant tumors are susceptible to metabolic therapies or targeting autophagy51. Together, this analysis provides targets that are impacted by the RB-pathway that could yield clinically relevant vulnerabilities.There is a large and expanding literature that CDK4/6 and RB activities are associated with biological features beyond cell cycle. Due to the limited genetic events targeting RB, gene expression analysis provides a more statistically-powerful approach to mine for features that are associated with pathway status. Utilizing this approach a large number of genes positively and inversely correlated with the CDK4/6-RB integrated signature can be identified. Interestingly, while there are some differences between tumor types the directionality of these correlations is surprisingly consistent. By analyzing the features that are positively correlated it suggests vulnerabilities that could be particularly relevant in targeting cells with cell cycle deregulation. These analyses encompass cell cycle genes  that have been shown to be preferentially actionable against https://www.cbioportal.org/datasets. These data consist of 31 histologically distinct tumor types. Oncoprint graphs were generated using the ComplexHeatmap function in R. The correlation between RB1 and CDKN2A gene expression was calculated using Pearson correlation coefficient, where “R” indicates the correlation coefficient with the associated p-value. Mutual exclusivity was determined using log odds ratio with the associated p-value. The NeoPalaAnna data were downloaded from the gene expression omnibus (GSE93204) and Metabric data were downloaded from cbioportal.org.All the TCGA datasets were acquired from cBioportal from the PanCancer Atlas Study cis gene order. The gene expression levels of RB1 were stratified by deep deletion, single copy loss and wild-type gene status. Box plots show the median, inter-quartile range and minimum/maximum data points for all figures. A two-sided, Student’s t-test was performed in R to find the significance as represented in the boxplot. Similar analysis was performed with survival data for each cancer types. Kaplan–Meier Survival analysis between wild-type and heterozygous gene loss was performed using the “survival” package in R. Statistical significance was determined by a log-rank test.All the genes present on Chromosome-arm 13q were obtained using the biomaRt package from Bioconductor. The information regarding the copy number variance files were downloaded from TCGA Pan-cancer analysis for each tumor type. The frequencies of heterozygous or homozygous deletion were mapped in the p < 0.05). These genes were filtered with identically treated RB deleted MCF7 cells, to define genes significantly repressed in an RB-dependent fashion (n = 362 genes). These genes were applied to the METABRIC Gene expression dataset to evaluate performance in clinical tumor specimens. Genes with a maximum correlation value less than the mean of the maximum correlation values, were filtered out and the remaining genes were used as CDK4/6 integrated signature totaling (n = 182 genes).MCF7 cells were obtained from the ATCC before 2010. The presence of mycoplasma was routinely assessed (every 3–6 months) using DAPI staining methodology on fixed cells. The cells retain estrogen receptor and harbor the morphology of MCF7 cells; the STR testing was performed on Feb 14, 2020 to confirm identity. The CRISPR-mediated deletion was achieved using guide sequences designed to target exon 2 of RB1 (CACCGAGAGAGAGCTTGGTTAACTT). A CAS9 expressing plasmid and RB1 target plasmid were co-transfected and single cell clones were developed. The targeting of RB was confirmed by immunoblotting and immunofluorescence as we have published. Parental MCF7 cells and those rendered RB-deleted by CRISPR-mediated gene targeting were treated with vehicle control or 250 nM palbociclib for 48 h. RNA recovered from duplicate biological samples were subjected to Illumina-based RNA sequencing (data is deposited in GEO under the manuscript title). The resultant Fastq files were processed using HTSeq. The RNA seq count files were then normalized by counts per million (CPM) using the edgeR package in R. Those genes that are downregulated in MCF7 cells treated with palbociclib were identified  were considered for this analysis. All the bootstrapped genes across all cancer types were hierarchically clustered based on their corresponding correlation coefficients to produce five distinct clusters. Gene ontology and transcription factor enrichments were determined using ENRICHR (https://amp.pharm.mssm.edu/Enrichr/).The Pearson correlation between each gene, with respect to the average gene expression of CDK4/6-RB integrated signature genes, was calculated for each cancer type. For an unbiased analysis, a bootstrapping algorithm was used by sampling genes 10,000 times with replacement. From this analysis, the lower limit and upper limit in a 95% confidence interval was used as cutoff with genes whose Pearson correlation coefficient is lesser than the lower limit being negatively correlated, and genes whose Pearson correlation coefficient is greater than the upper limit being positively correlated with CDK4/6 integrated signature genes. Only those genes whose correlation with CDK4/6 integrated signature genes are significant (t-test of CDK4/6 inhibitor treated relative to DMSO control to generate a volcano plot. The corresponding genes that were highly negatively correlated (represented as blue) and highly positively correlated (represented as red) with the cell cycle genes, from the bootstrapped gene lists for breast cancer (BRCA).For the analysis of the MCF7 dataset, the log fold change and the p-value were calculated using a standard two tailed student p_val(i)) Where, for each gene i, the corresponding weight W(i) is the product of the Pearson correlation coefficient of the gene (CC(i)) and corresponding p value). Next, gene set enrichment analysis (GSEA) using the pre-ranked gene set along with the corresponding weights was performed to find Gene Ontology (GO) terms. Networks showing the relationship between GO terms were generated using the java-based application Cytoscape program called Enrichment Mapper. Common GO terms were then clustered and annotated.For each cancer type, the highly positively correlated and highly negatively correlated genes were combined and their corresponding weights were calculated using the formula:W(i)=CC(i)*(−log10(The number of samples is provided in the figure or employed the totality of the tumor population. Statistical approaches and replicates are described in the methods above, or in the figure legends.Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesReporting SummarySupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Peer Review File


GAD1 was described as a candidate mutation in a single family diagnosed with autosomal recessive spastic cerebral palsy-1 . Following the ascertainment of a further branch of the CPSQ1 kindred, we found that the previously reported GAD1 variant did not segregate with the neurological disease phenotype in the recently ascertained branch of the kindred. Following genetic linkage studies to map autozygous regions and whole-exome sequencing, a missense variant  in the HPDL gene was detected and found to segregate with disease status in both branches of the kindred. HPDL encodes a 371-amino acid protein (4-Hydroxyphenylpyruvate Dioxygenase Like) that localizes to mitochondria but whose function is uncertain. Recently, biallelic loss of function variants and missense substitution-causing variants in HPDL were reported to cause a childhood onset progressive spastic movement disorder with a variable presentation. These findings suggest that HPDL-related neurological disease may mimic spastic cerebral palsy and that GAD1 should not be included in diagnostic gene panels for inherited cerebral palsy.A subset of individuals diagnosed with cerebral palsy will have an underlying genetic diagnosis. Previously, a missense variant in  et al. report that a novel candidate mutation in the HPDL gene (but not GAD1) segregates with disease status within a kindred in which a locus for autosomal recessive spastic cerebral palsy-1  was mapped previously (in part of the kindred).Morgan   Cerebral palsy is a common cause of childhood neurodisability that is characterized clinically by permanent abnormalities of motor activity and posture. It typically includes spasticity and often intellectual disability and epilepsy, and results from non-progressive disturbances to the fetal or infantile brain . Here, we provide further genetic evidence to demonstrate that CPSQ1 is not caused by GAD1 but by a missense substitution in a recently described gene, HPDL.More than 20 years ago, Molecular genetic studies were undertaken in 15 individuals from a large consanguineous British Pakistani kindred that was initially ascertained as two distinct families but later established to be part of a larger kindred. One of the families (Branch A) was originally described in the clinical report by GAD1 candidate region reported in GAD1 missense substitution was performed. Subsequently, a genome-wide linkage scan was carried out using Affymetrix Genome-Wide Human SNP 5.0 microarrays in a total of six affected individuals [five affected individuals from Branch A  and one affected individual from Branch B (V: 10)]. Homozygosity mapping analysis was then performed and homozygous regions were identified using HomozygosityMapper (http://homozygositymapper.org)  and sequencing on the HiSeq 2500 (Illumina) with 100 bp paired-end reads. The sequences were aligned to the reference genome (GRCh37), with Novoalign (Novocraft Technologies Sdn Bhd). Duplicate reads, resulting from PCR clonality or optical duplicates, and reads mapping to multiple locations were excluded from downstream analysis. Depth and breadth of sequence coverage were calculated with custom scripts and the BedTools package. Single-nucleotide variants and small insertions and deletions (InDels) were identified and quality filtered within the SamTools software package and in-house software tools. All calls with a read coverage of <4 and a phred-scaled SNP quality of <20 were filtered out. Variants were annotated with respect to genes and transcripts with the Annovar tool . FurtherTM. Sanger sequencing was then performed using the same primers, primer sequences are available on request. Sanger sequencing was performed using BigDye Terminator Cycle Sequencing Kit, version 3.1 (Applied Biosystems) and analysed on an ABI 3130XL DNA analyser (Applied Biosystems).Amplification of genomic DNA for Sanger sequencing for three individuals  was performed by standard PCR methods. PCR clean-up was performed with MicroCleanThe authors confirm that all the data supporting the findings of this study are available within the article and readily available upon request.The kindred pedigree is shown in GAD1 as a candidate mutation . Following the ascertainment of Branch B, we performed extended segregation analysis using microsatellite markers mapping to 2q24-q31 and genotyped the c.36G>C variant across both branches. This confirmed the finding that c. 36 G > C variant segregated with disease status in Branch A (including the newly diagnosed sibling V: 8) but that in Branch B two affected individuals (V: 10 and V: 11) were either heterozygous (V: 10) or homozygous wild type (V: 11) and the father (IV: 3) was homozygous wild type . Unless the autosomal recessive neurological disorder diagnosed in Branch A and Branch B were different, this excluded GAD1 as the cause of the disease in this kindred.Previous linkage studies and sequencing analysis in Branch A  from Branch A and V: 10 from Branch B. Analysis using homozygosityMapper revealed two areas of extended homozygosity shared between all affected individuals. A 551 761-bp region on chromosome 10 between SNPs rs2036919  and rs11013778  and a much larger 17 596 867 bp region on chromosome 1 between SNP markers rs1046988  and rs6687842  .https://etheses.bham.ac.uk//id/eprint/3068/) comparisons with dbSNP build 134, the 1000 Genomes Project database (The 1000 Genomes Project Consortium), Exome Variant Server (http://evs.gs.washington.edu/EVS/) and our in-house dataset, identified 61 homozygous variants in the affected individual , independent analysis of the exome-sequencing results for two affected individuals (V: 10 and V: 11) in Branch B also prioritized this variant as the best candidate mutation within the autozygous segment.To identify a causative pathogenic variant, we proceeded with exome sequencing in one affected individual (V: 5) from Branch A. Exome sequencing revealed 23 469 variations of which 9869 were novel or rare (<0.01) sequence changes. At the time of initial analysis  and deleterious in SIFT (https://sift.bii.a-star.edu.sg). The affected Leucine residue  is conserved across multiple species . Variant classification according to ACMG criteria and assigning moderate evidence for pathogenicity for the results of segregation of the c.527 T > C; p. Leu176Pro substitution in both branches of the family resulted in a likely pathogenic classification for this variant  was identified in four affected siblings with symmetrical spastic cerebral palsy  with biallelic HPDL mutations . The rare c.527T>C, p. Leu176Pro variant detected in both branches of the family reported here has not been reported previously but other candidate pathogenic missense variants described by HPDL encodes the 4-Hydroxyphenylpyruvate Dioxygenase-Like protein that does not currently have a known function. HPDL transcript levels are high in the central and peripheral nervous system, a mitochondrial localization signal was predicted in the first 37 amino acids and exogenous HPDL was found to co-localize with mitochondria  in n = 7) adds significantly to the number of subjects with HPDL-associated disease currently in the literature (n = 17). In the original descriptions of affected children in Branch A, n = 17) reported by GAD1  detected previously in Branch A could not account for the disease phenotype in both branches of the kindred, we note that mice homozygous null for Gad1 die at birth with cleft palate and hypoxia, with omphalocele in about 50% , omphalocele (18%) and joint contractures (55%). Though it is possible that GAD1 variant status might modify clinical presentation within the two branches of the family described here, we note that these clinical features, including, epilepsy were not reported within the family.Though we report a single kindred, the large number of affected individuals  locus at 2q31.1 resulting from a mutation in the Brain Communications online.fcab002_Supplementary_DataClick here for additional data file.


Glioblastoma is the most aggressive form of brain tumors. A better understanding of the molecular mechanisms leading to its evolution is essential for the development of treatments more effective than the available modalities. Here, we aim to identify molecular drivers of glioblastoma development and recurrence by analyzing DNA CpG methylation patterns in sequential samples.DNA was isolated from 22 pairs of primary and recurrent formalin-fixed, paraffin-embedded glioblastoma specimens, and subjected to reduced representation bisulfite sequencing. Bioinformatic analyses were conducted to identify differentially methylated sites and pathways, and biostatistics was used to test correlations among clinical and pathological parameters.Differentially methylated pathways likely involved in primary tumor development included those of neuronal differentiation, myelination, metabolic processes, synapse organization and endothelial cell proliferation, while pathways differentially active during glioblastoma recurrence involved those associated with cell processes and differentiation, immune response, Wnt regulation and catecholamine secretion and transport.DNA CpG methylation analyses in sequential clinical specimens revealed hypomethylation in certain pathways such as neuronal tissue development and angiogenesis likely involved in early tumor development and growth, while suggested altered regulation in catecholamine secretion and transport, Wnt expression and immune response contributing to glioblastoma recurrence. These pathways merit further investigations and may represent novel therapeutic targets.The online version of this article (10.1007/s00432-020-03349-w) contains supplementary material, which is available to authorized users. Glioblastoma (GBM) is the most aggressive brain tumor exhibiting great variability at histopathological and molecular levels. Its development is related to the accumulation of somatic genomic rearrangements, mutations and copy number alterations (CNAs), accompanied by changes in epigenomic and gene expression profiles. In some cases, chromothripsis, a sudden catastrophic rearrangement involving one or a few chromosomes, may also play a role  method. Combining RRBS with next-generation sequencing (NGS), Klughammer et al.  reportedTesting key molecular markers . Leftover blocks were used for these molecular analyses after receiving approval (Number: 7517 PTE 2018 and 2019) from the Regional Clinical Research Committee.The characteristics of patients and specimens are summarized in Table In control group 1 (CG1), six postmortem FFPE normal brain specimens were included from the tissue archive of the Pathology Institute, UP. This unideal choice was necessitated because no surgically dissected normal brain or other neurological disease control FFPE specimens were available. In control group 2 (CG2), DNA CpG methylation data of five brain specimens obtained during epilepsy surgery were included by downloading from the EBI European genome–phenome archive (accession number: EGAS00001002538) . DNA quantitation was carried out using a Qubit™ 1X dsDNA HS Assay Kit on a Qubit 3 Fluorimeter . The distribution of DNA fragments was determined by an Agilent Genomic DNA ScreenTape Assay on an Agilent 4200 TapeStation System .https://www.ebi.ac.uk/ena, Primary Accession: PRJEB38380, Secondary Accession: ERP121800). The glioma CpG island methylator phenotype (G-CIMP) was excluded with high probability in the GBM1 and GBM2 cohorts by adapting the eight gene method for bisulfite-converted sequence data  according to the manufacturer’s instructions. To compensate for higher degrees of fragmentation, we increased from the recommended 200 ng to higher amounts (350–400 ng) of input DNA. DNA digestion by Msp1 was then followed by fragment-end repair and adaptor ligation. The amount of effective library was determined using the Kapa Sybr Fast qPCR kit  on a StepOnePlus Real-Time PCR System . Samples with similar quantitative (q)PCR threshold cycle (Ct) values were multiplexed in pools of eight. The pools were subjected to bisulfite conversion, followed by a second qPCR to determine the enrichment amplification cycles for the final PCR on a GeneAmp PCR Systems 9700 . After confirming the adequate fragment size distributions on the 4200 TapeStation System and the concentrations by the Qubit 3 Fluorometer, the amplified libraries were sequenced using the NextSeq 500/550 High Output Kit v2.5 (75 cycles) on a NextSeq 550 machine . Raw sequencing data were uploaded to the European Nucleotide Archive  were correlated with histological characteristics using the Kruskal–Wallis and Mann–Whitney We compared DNA CpG methylation patterns in normal brain tissues and IDH-wild-type GBM specimens at initial diagnosis GBM1) and at first recurrence GBM2). Two control groups were initially considered. CG1 included the DNA CpG methylomes of six postmortem normal brain regions from individuals who passed away from non-neurological causes. CG2 included the DNA CpG methylomes of five FFPE brain tissues obtained during epilepsy surgery and deposited in a publicly available database . For comparison, the DNA fragment rates above 2000 bp were 87.15% in freshly drawn total blood and 70.18% in buffy coat (Supplementary Table 1).The mean bisulfite conversion rate that reflects the chemical conversion of unmethylated cytosine to uracil was 98.48% (Supplementary Table 2). Using the spike-in controls, the mean underconversion rate was 1.32%, and the mean overconversion rate was 1.70% (Supplementary Table 2). At an average alignment rate of 69%, the mean number of informative CpGs per sample was 20,741,979 and the median number of CpGs was 16,574,809 in the non-deduplicated raw data, representing over ten times higher than expected figures due to duplications during library amplification. Deduplication is not recommended, since it could result in biases in the CpG representation and a loss of information. Instead, 19,936 sites with overlapping SNPs were removed and CpGs with extremely high coverage were filtered out for the correction of duplicated sequences during bioinformatics preprocessing.There was a trend for fewer informative CpGs in samples with lower quality of DNA. In CG2 , but reached significance in the GBM2–GBM1 (p = 0.046) and GBM2–CG2 (p = 0.032) comparisons (Supplementary Table 3).Overall, a shift toward hypomethylation was observed when comparing the controls and the sequential tumor samples . The methylation differences showed only a trend in the GBM1–CG2 comparison . We primarily focused on differential methylation rates in gene promoters comparing CG2–GBM1, CG2–GBM2, and GBM1–GBM2 in all analyses.p-values of ≤ 0.05 in the scatterplots in the three group-wise comparisons.Differential methylation on the site and region levels revealed no FDR corrected p = 8.38E-05) and cellular responses to the fibroblast growth factor (FGR) . There were, however, also genes showing higher degrees of promoter methylation, but with lower degrees of significance. For instance, 17 different promoters in genes associated with nucleic acid-templated transcription had hypermethylation in GBM1 compared to CG2 (mean p = 0.0079). Eighteen promoters in genes associated with the regulation of different nucleobase-containing compound metabolic processes were hypermethylated (mean p = 0.0088). Furthermore, there were 19 hypermethylated promoters of genes associated with pathways of neuron morphogenesis and differentiation in GBM1 compared to CG2.In the GO analyses, hypermethylation was observed within promoters of genes related to pathways of neuronal differentiation and morphogenesis, and transcription and metabolic processes in GBM1 compared to CG2. The most significantly hypermethylated gene promoters were related to gastrulation regulation , synapse assembly , endothelial cell proliferation  and myelination .The GBM2–CG2 comparison showed pathways with gene promoter hypermethylation associated with transcription regulation, cell adhesion and morphogenesis and embryonic development in the GBM2 samples. Pathways which showed the most significant hypermethylation in promoters were associated with appendage morphogenesis and limb development . The pathways with numerically the most promoters hypermethylated were associated with transcription regulation by RNA polymerase II and cell adhesion processes. Pathways with hypomethylated gene promoters in GBM2, compared to CG2, included a few associated with purine and pyrimidine nucleobase transports (SLC28A1), Golgi transports  and allantonin catabolic processes (ALLC).Comparing GBM1 and GBM2, the GO analysis revealed several pathways of biological relevance. Pathways with gene promoter hypermethylation in the recurrent compared to the primary tumors included genes related to regulation of the Wnt pathway, catecholamine secretion and transport, and cellular response, signaling and communication. The most significantly hypermethylated pathways in the recurrent samples were those associated with catecholamine secretion regulation , catecholamine transport  and signaling receptor activity regulation  as well as those negatively regulating the canonical Wnt signaling pathways , and some Wnt ligands and receptors. However, the pathways with numerically the most hypermethylated promoters in GBM2 were those associated with regulation of the stimulus response , cell communication , signaling  and localization .p values were noted in pathways linked to the regulation of lymphocyte-mediated immunity , natural killer (NK) cell-mediated cytotoxicity  and regulation of cell killing . In addition, several other important regulators of immune response were hypomethylated  in the recurrent samples compared to the initial GBMs. Finally, the most hypomethylated and most numerous  promoters, although with the least significant p values (mean p = 0.0098), were detected in cell proliferation pathways in GBM2.Pathways with promoter hypomethylation in the recurrent compared to the initial tumors included genes related to both the innate and adaptive immune responses, cellular processes and cell differentiation. The most significant The LOLA program was run to enrich for genomic region sets and regulatory elements relevant to the interpretation of functional epigenomics data (Sheffield and Bock p = 0.08), but not in the GBM2 samples (p = 0.737). Neither Mann–Whitney nor Pearson’s correlation analysis showed a link between TIL and mitotic rate.We detected no association between T1–T2 and gender or the age of patients, or T1–T2 and morphological subtype, mitotic rate, microvascular proliferation or necrosis of the tumors. However, a trend for association was found between T1–T2 and the amount of tumor infiltrating lymphocytes (TIL) in the GBM1 samples , these samples worked well in RRBS. However, because DNA quality was profoundly further compromised in the postmortem CG1 (mean fragment rate above 2000 bp: 5.91%), and the number of methylated CpG sites proportionally decreased with increasing fragmentation consistent with previous reports  in the pathway of positive regulation of endothelial cell proliferation, a factor contributing to angioneogenesis, and thereby promoting GBM growth  and receptors  were also significantly less methylated in GBM1 as compared to GBM2. In contrast, promoters of other Wnt ligands  and receptors  were less methylated in GBM2 than in GBM1. Although not in sequential samples, but in GBM and control brain comparisons, a differential methylation of Wnt genes  and pathways, and both up-  and downregulation of Wnt pathway transcripts  have been noted  in genes defining catecholamine secretion and transport in GBM1 compared to GBM2. Monoamine signaling in glioma initiating cells participates in hijacking normal developmental mechanisms and promotes tumor development. Synaptic monoamines in the GBM microenvironment influence tumor growth and angiogenesis  in immune pathway genes regulating leukocyte, lymphocyte and NK cell-mediated immunity. However, there were other immune-regulatory processes such as macrophage inflammatory protein production and CD8 + T cell proliferation that appeared more active (with promoters more hypomethylated) in GBM1 than in GBM2. These data are in consensus with the detected association between TIL in GBM1 and T1-T2, and align with previous observations concerning differential activity of various immune pathways during the development and progression of GBM . The results of the first (cross-platform) analysis revealed that promoters in genes of pathways involved in embryonic development, immune regulation and Wnt signaling were less methylated (presumably more active) in the TCGA GBM samples than in the CG2 controls. The results of the second analysis showed less methylated (presumably more active) promoters in genes of pathways involved in stem cell proliferation and cell dedifferentiation, intracellular regulatory and metabolic processes, negative regulation of apoptosis, cell adhesion and T cell polarity as well as migration in the TCGA recurrent compared to the primary samples. In contrast, promoters of genes in pathways involved in endothelial cell proliferation, negative regulation of the execution phase of apoptosis, T cell proliferation, cell–cell signaling, neuronal differentiation, and regulation of G protein-mediated signaling  were less methylated (presumably more active) in the TCGA primary than in the recurrent samples. Considering the technical limitations and interpretive difficulties when comparing data from various platforms and also results from small cohorts, the outcome of the TCGA sample analyses in overlap with ours lends further support to our conclusions.Finally, we also found support to our observations by comparing the array-based DNA CpG methylation data of TCGA GBMs to the sequence-based methylomes of our CG2 controls  and histone proteins  likely relevant to CSC differentiation and GBM development . Supplementary Table 3b. Methylation data of postmortem control samples (CG1). These tables show DNA CpG methylation data in GBM1, GBM2 and CG1. Supplementary Table 4. Sample coverage data. This table summarizes NGS coverage data in paired GBM samples (XLSX 41 kb)Below is the link to the electronic supplementary material.