The prevalence of cytotoxic tumor infiltrating lymphocytes (TILs) has demonstrated prognostic value in multiple tumor types. In particular, CD8 counts (in combination with CD3 and CD45RO) have been shown to be superior to traditional UICC staging in colon cancer patients and higher total CD8 counts have been associated with better survival in breast cancer patients. However, immune infiltrate heterogeneity can lead to potentially significant misrepresentations of marker prevalence in routine histologic sections. We examined step sections of breast and colorectal cancer samples for CD8+ T cell prevalence by standard chromogenic immunohistochemistry to determine marker variability and inform practice of T cell biomarker assessment in formalin-fixed, paraffin-embedded (FFPE) tissue samples. Stained sections were digitally imaged and CD8+ lymphocytes within defined regions of interest (ROI) including the tumor and surrounding stroma were enumerated. Statistical analyses of CD8+ cell count variability using a linear model/ANOVA framework between patients as well as between levels within a patient sample were performed. Our results show that CD8+ T-cell distribution is highly homogeneous within a standard tissue sample in both colorectal and breast carcinomas. As such, cytotoxic T cell prevalence by immunohistochemistry on a single level or even from a subsample of biopsy fragments taken from that level can be considered representative of cytotoxic T cell infiltration for the entire tumor section within the block. These findings support the technical validity of biomarker strategies relying on CD8 immunohistochemistry. Breast and colorectal cancers are the second and third most common malignancies worldwide, respectively. Between 2008 and 2015, breast cancer incidence has increased by more than 20%, while mortality has increased by 14% and it now represents one in four of all cancers in women [Disease progression in cancer patients is determined not only by the histologic and molecular features of the tumor but also by the host response, particularly the immune response. Observations that inflammatory cell density is higher in tumor tissue than in non-adjacent normal tissue in breast cancer patients  and thatIn addition to the prognostic impact of CD8 levels across multiple cancer indications, densities of intratumoral CD8+ T cells are associated with response to anti-PD-1 (pembrolizumab) treatment in melanoma and mismatch repair deficient cancers, including colon cancer ,24. TherAlthough most studies show improved prognosis with increased tumor-associated cytotoxic T cells, some reports have demonstrated conflicting results. For non-small cell lung cancer, several studies associated increased CD8 with improved patient outcomes ,26,27, bWhen a biomarker such as CD8 is employed in a clinical setting, the effects of assay variability, whether attributable to analytical characteristics of the assay itself or due to pre-analytic sample properties such as sample preparation and sample type , could potentially have broader implications for clinical trial study design, study conduct, and the interpretation of results at the end of trial ,35,36,37in silico biopsy sampling of these sections to determine CD8 variability within a tumor block and between simulated biopsy samples. Numbers of CD8+ T cells were obtained by digital image analysis for each level and simulated biopsy. CD8 counts between levels of a tissue sample were fit to a linear variance model to determine the statistical significance of the CD8 count variability. Similarly, in simulated core biopsies, the degree of variability in CD8 counts was assessed and related to the overall ‘true’ block count to determine the number of cores necessary for adequate sampling. Our results show that CD8+ T cell numbers are highly homogenous throughout colon and breast cancer tissue section and that a single virtual core biopsy can potentially adequately represent tumor-associated cytotoxic T cell prevalence, though estimates improve with increasing sample number.In light of these practical considerations: what constitutes an adequate histologic evaluation of immune contexture, particularly in characterizing cytotoxic T cell infiltration of a tumor for prognosis, predicting response to immunotherapy, and for monitoring on-treatment pharmacodynamics? To inform practice of histologic T cell biomarker interpretation, we examined step sections of breast and colorectal cancer samples for CD8 T cell prevalence by immunohistochemistry, and performed Formalin-fixed paraffin-embedded (FFPE) breast cancer and colon cancer samples were procured. Breast cancer samples were procured from Avaden Biosciences and included both ductal (8) and medullary (4) carcinoma cases. Cases contained between 20% and 80% tumor in the regions analyzed by visual estimate of area. Patient ages for breast samples ranged from 40–82 years and AJCC stages I-IV were represented. Colorectal cancer samples were procured from Conversant Bio and included moderately differentiated adenocarcinoma (9), mucinous carcinoma (1) and rectal (2) carcinoma cases. Samples contained between 20% and 60% tumor in the regions analyzed by visual estimate of area. Patient ages ranged from 43–89 years, and stages I and II disease were represented.Tissue blocks were serially sectioned and four serial levels were taken approximately every 10 μm until the block was exhausted or tissue significantly reduced yielding eight sets of 4 serial sections per case available for staining. For any given block, the second level of each set of serial sections was stained for CD8, leading to an assessment of CD8 prevalence every 25 μm .Immunohistochemistry (IHC) was performed on 4 μm thick formalin-fixed, paraffin-embedded tissue sections mounted on glass slides. All IHC steps were carried out on the Ventana Discovery XT automated platform . Sections were treated with Cell Conditioner 1, standard time, and then incubated in primary antibody, CD8  at a working concentration of 0.157 mg/ml for 60 minutes at room temperature. Specifically bound primary antibody was detected by the OmniMap anti-rabbit HRP detection kit, followed by ChromoMap DAB . The sections were counterstained with Hematoxylin II , dehydrated, and cover-slipped. Positive staining controls were performed in parallel using human tonsil and negative controls were performed using IgG1 isotype antibody.2 in size. Rectangular regions that overlapped with at least 0.7 mm2 of manually identified region were analyzed. Individual cells were identified using an algorithm based on radial symmetry [Whole slide images were acquired with a Nanozoomer 2.0-HT automated slide scanning platform  at 200x final magnification. Scanned slides were analyzed in the Matlab software package  as 24-bit RGB images. Tumor regions were manually identified at a macroscopic level. Simulated core biopsies were identified by creating a grid of rectangular regions over the entire image, each approx. 2 mmsymmetry . Each cesymmetry .All statistical analyses were conducted in the R environment for statistical computing . In addiResampling methods were employed to answer questions about the utility of using a smaller number of sections for determining CD8+ status. The mean CD8-positive percent staining value across sections within a tumor sample was treated as the true expression value for that specimen, and the median value across all tumor samples was selected a candidate cut-off for CD8+ staining. Resampling was performed 1000 times, (i) by resampling smaller numbers of sections—e.g., one or two from the original 8—with replacement within the original, fixed set of 25 tumor samples to assess the effects of within-tumor heterogeneity, and (ii) by resampling with replacement first tumors and then sections within tumors to better assess the effects of biological and technical variability in determining CD8+ status in future samples of patient tumor blocks.2, each with a minimum tumor area of at least 33% . A key question was how many simulated smaller biopsies would be needed to adequately approximate the CD8 IHC staining and assay performance of (i) the entire slide and (ii) the entire tumor block (pooled across slides). Sampling 1000 times without replacement, the mean CD8 percent positive staining was estimated using increasing numbers of cores (1–5 cores) and by taking either the mean or maximum of the subsampled biopsy fragments as an estimate summary measure. To allow for less-biased resampling without replacement of up to 5 cores, analysis (i) was restricted to 183 slides with at least 15 identified fragments  was calculated as a summary measure. Local regression (loess) fits were also obtained in order to characterize the variability associated with sample fragments as a function of mean CD8 percent staining [A total of 198 slides sectioned from the 25 blocks were further subdivided into simulated smaller biopsy fragments ("cores") of maximum size ~2 mmstaining . Assay pIn order to determine whether sampling error contributes to variation in intratumoral T cell counts, we sectioned through and enumerated CD8+ T cells in 13 primary colorectal adenocarcinoma and 12 breast carcinoma  cases (1 FFPE block per case). Step sections of breast and colorectal cancer samples were taken at approximately 25 μm intervals from FFPE samples and stained for CD8 using DAB-based chromogenic immunohistochemistry . Image aFrom the 12 breast cancer cases, 3 were noted to have significant tissue loss on deeper levels. Specifically, deepest sections (level 8) from two cases showed less than 40% of tissue remaining compared to the initial level. A separate case showed approximately 30% of tissue compared to the initial level on levels 7 and 8. Only one colon cancer sample showed significant tissue loss on one of eight levels. Since these changes could potentially introduce artifactual variability, statistical analyses that both included and excluded these levels were run.Breast cancer samples showed a wide range of cytotoxic T cell infiltration varying from less than 1%  to greater than 50%  marker-positive lymphocytes. Histology showed diffuse T-cell infiltration with most breast cancer cases showing CD8+ cells in comparable amounts at the tumor edge and center. Medullary carcinoma cases showed characteristically high lymphocyte infiltration and high CD8+ area , compared to ductal adenocarcinoma .Colorectal cases showed, in general, somewhat less cytotoxic T cell infiltration than breast cancer cases . The majority of CRC cases (12/13) showed less than 10% CD8+ T cells on any level in contrast to breast cancer samples where 50% (6/12) of cases showed less than 10% CD8+ prevalence. The maximum amount of CD8+ T cells was 13.6%. In contrast to breast cancer tissues, CD8+ T cells in colon cancer cases were confined largely the stroma with few infiltrating lymphocytes among epithelial cells.Assessment of full-face sections showed greater variability in CD8+ T cell prevalence between cases than between levels from an individual case. This observation also held when cases were divided by histologic type, such that cytotoxic T cell prevalence on serial sections varied more greatly between cases of ductal adenocarcinoma than within a case of ductal adenocarcinoma . HoweverTo determine whether a single slide is sufficient to assess the status of CD8+ T cell abundance, we next assessed the performance of this assay benchmarked against a median cut-off. In the resampling-based analysis, pooling breast and colon samples, a median (50th percentile) cutoff of 5.9% percent CD8+ staining was calculated for determining a patient’s CD8+ status. With a patient’s average CD8 expression computed across all sections being considered "truth,” patients were classified as CD8-high or CD8-low depending on whether or not their mean expression was above or below the median cut-off determined by the larger sample. Relative to the CD8 status determined by the mean CD8 expression, classifying patient samples by taking even just one slide at random resulted in 94.8% (95% CI: 88.0% -100%) positive agreement (concordance), with 94.5% simulated sensitivity in detecting “CD8-high” patients and 95.1% simulated specificity in detecting “CD8-low” patients . Similar2 were digitally generated within manually selected tumor regions and the percentage of CD8+ cells were calculated for each field. Surprisingly, sampling just 1–5 biopsy fragments from an individual slide, and across slides, recapitulated CD8 staining observed both at the slide and tumor block level, respectively , and were thus able to approximate the standard deviations associated with sampling the subsets of cores relative to the rest of the tumor sample. Differences in means were centered around zero (unbiased), with decreases in variability again observed with increased sampling  and incrn”-like convergence, some researchers may alternatively use the maximum percent staining value obtained on from a small number of biopsies as a summary measure. Our results demonstrate that the use of order statistics such as maxima should be carefully considered or avoided altogether if one is trying to get a representative assessment of overall staining within a tumor or individual. Using the maximum over increasing numbers of biopsies resulted in biased overestimates of CD8 staining relative to the mean CD8 positivity and in estimates which rapidly diverged from the mean +/- 1SD range of CD8 staining of the slide or block  curves were used to display assay performance of the CD8 staining estimates obtained from the biopsies over a range of potential candidate staining cut-offs that could be considered in a clinical trial setting . Here, the mean CD8 staining of a slide or block was used as the gold standard or "truth" against which CD8 positivity or negativity as determined by a set of simulated core biopsies was evaluated for a given cut-off. In terms of being able to correctly classify patients as being CD8-positive or CD8-negative, a high level of sensitivity and specificity was observed when comparing results from a single biopsy fragment to a sample’s status based on evaluation of the whole slide or block. For example, using a 5% cut-off, relative to the result obtained from a slide, the value for the biopsy fragment displayed on average 85.6% sensitivity and 89.9% specificity over 1000 rounds of simulation . Taking Predictive diagnostics for cancer immunotherapies have focused on the tumor-immune microenvironment and its composition. As such, histologic assessment of tumors and their immune contexture is becoming central to prognosticating clinical behavior in patients with solid tumors both by determining the amount of immune infiltrate and its composition, as well as prevalence of actionable immunotherapy targets, e.g. PD-L1, and prognostically relevant immune cell subtypes, including CD8+ T cells. However, variable sampling and interpretation methods including scoring algorithms and inter-pathologist variability can potentially confound histology as a prognostic method. As well, interpretation of more limited samples, such as core biopsies, raises questions about sampling adequacy and error. However, the extent and potential effect(s) of sample type and spatial heterogeneity of tumor immune infiltrates has not been detailed. The clinical and scientific importance of TIL assessment in breast cancer has been underscored by recent efforts to standardize histologic interpretation of TILs in patient samples, but it has been noted that TIL heterogeneity and adequacy of core biopsy samples versus tissue sections has not been formally characterized .CD8+ cytotoxic T cells in particular have received attention not only because of their known role as cytolytic agents and demonstrated reactivity to tumor-derived self-epitopes  but alsoOur results demonstrate that the prevalence of CD8+ T cells is highly consistent within a standard sample block. Comparing whole slide counts of step sections from a given tumor block, CD8+ T cell percentage varied within 8% between all levels of a given breast cancer sample and within 2% between all levels of a given colorectal cancer sample. Also, we find, based on a linear-effects model and variance component analysis, that of any observed variability across all samples or within a tumor type, less than 1% can be attributed to section-to-section variability. We conclude that, for this particular IHC assay, CD8+ cell prevalence on a single slide can be representative of the CD8+ status of the entire block.in silico designation and analysis of 2 mm2 sections of tumor area to simulate biopsy sampling, we found that (1) one biopsy sample can approximate CD8 prevalence to within one standard deviation of the block mean in greater than 75% of all analyzed cases, (2) using multiple cores improves performance up to three cores (best), and (3) the mean CD8+ cell percentage for multiple biopsies was a less variable and less biased predictor of CD8 status for a given tumor sample than the maximum value. For three of four cases in which a single simulated core biopsy failed to estimate the CD8 prevalence to within 1 standard deviation of the corresponding slide or block, a heterogeneous distribution of CD8+ cells, concentrated primarily at the tumor margins, was noted in each slide of each case. Significant tissue loss was noted in one remaining case. This suggests that spatial heterogeneity can potentially confound interpretation of biopsies for immune cell prevalence but only in a minority of cases. However, we find that additional biopsy samples can significantly improve accuracy. For instance, where single core simulations in one case generated estimates to within 1 SD in only approximately 65% of instances, addition of a second core and calculation of mean CD8+ cell percentage generated accuracy to within 1 SD of the slide mean in approximately 85% of instances. Addition of a third core further improved accuracy to over 90%. Such improvements were observed in all cases where single biopsy simulations were accurate to within 1 SD less than 80% of the time.While evaluation of CD8 prevalence on a standard slide may generate consistent results, the adequacy of biopsy samples for evaluation of immune cell prevalence has not been extensively characterized. Biopsy sampling, particularly core biopsy sampling, has traditionally been examined in the context of solid tumor diagnosis and phenotyping. Additionally, core biopsies are routinely employed for assessing changes in immune cell numbers and activity in immunotherapy studies. In breast cancer, core biopsies have been shown to correlate poorly with whole slide sections for assessment of some histologic markers such as Ki-67 but well with others such as ER and HER2 . As wellHowever, if multiple biopsies are available for interpretation, is calculation of a mean CD8+ cell percentage the best for interpretation? We explored the utility of taking the maximum CD8+ cell percentage value obtained from multiple cores but found calculation of mean CD8+ cell percentage to be more accurate. With increasing numbers of samples, the mean CD8+ cell percentage reduces variability over the dynamic range of the assay and improves sensitivity with minimal change in a low diagnostic false positive rate across multiple diagnostic cut-offs . As such, while mean CD8+ cell percentage is a highly specific method, sensitivity can be reduced at higher diagnostic cutoffs. Conversely, when using maximum CD8+ cell percentage, increasing the number of samples analyzed improves sensitivity but dramatically reduces specificity across all cut-offs. These relationships hold true for biopsy sample estimates relative to both corresponding slides as well as blocks.Since samples for the current study were procured, the availability of tumor sections of adequate amount and integrity was limited and only less than 15 cases for each tumor type could be evaluated. Expanding the number of samples could better characterize any potential variability in step sections or biopsy samples. However, given the high degree of consistency in the existing samples, we speculate that any further differences would be minor and that the limited number of samples in the current study does not significantly detract from the results. Also, in the current study we could only examine one block from a given tumor. While the degree of cytotoxic T cell heterogeneity was not significant within a given block, we cannot make conclusions regarding the homogeneity of CD8 infiltration within an entire tumor. At the time of this writing, the degree of histologic CD8 heterogeneity from standard pathology sampling of an entire tumor specimen has not been documented. Performing the current analysis across multiple blocks/sections from a tumor would add further insight into the prognostic value of CD8 immunohistochemistry in tumors as well as potentially inform sampling methods by pathology services for routine histologic analysis. In addition, our methods may be more widely applicable and inform development of other tissue-based biomarkers. For instance, Foxp3+ cell prevalence in tumor samples either alone or in ratio to CD8+ cell counts has gained attention as a potential tissue-based prognostic marker in multiple tumor types. Studies in breast cancer have documented improved pathologic complete remission (pCR) and disease-free survival in HER2+ or triple negative breast cancer (TNBC) patients with CD8+ to Foxp3+ cell ratio (CFR) greater than 1 when assessed by immunohistochemistry . As wella priori the analytical performance of any biomarker assay that may be deployed in clinical practice. An assessment of assay performance can also include the effect of biopsy type  on the results of the assay. Additionally, information about assay performance can also be included or accounted for when designing a clinical trial. While variability over the dynamic range of the assay in a patient population may be informative, it is of particular interest to understand assay performance around a given cut-off. Simulations can be run in order to assess if the assumed biomarker-treatment effect relationship of a therapy being interrogated is robust to assay performance issues given the cut-off and the range of expression in the patient population of interest. Once the clinical trial is ongoing, (blinded) assay data may also be evaluated in order to ensure that biomarker prevalence estimates and assay performance is as expected as during the design stages of the clinical trial and to guide potential risk mitigation strategies during enrollment.Despite the limitations associated with the number of tumor samples included in this analysis, our results highlight the practical importance of understanding in silico biopsy modeling, we find that immune cell prevalence estimates can be accurately represented with just one biopsy sample and that accuracy improves with increasing sample number when the mean CD8+ cell percentage among the biopsy samples is assessed. These findings not only support the technical validity of biomarker strategies relying on CD8 immunohistochemistry but also suggest standards for sample number adequacy and interpretation.Taken together, our findings show that CD8+ cell prevalence is highly homogeneous within a standard tissue sample and that evaluation of any slide from a given block can be considered representative of the CD8+ cell prevalence. Also, through S1 FigCD8 IHC repeated measures staining results for simulated core needles biopsies on 183 slides sectioned from 25 breast  and colorectal  carcinoma samples.(EPS)Click here for additional data file.S2 FigCD8 IHC repeated measures staining results for simulated core needles biopsies for 25 breast (red) and colorectal (blue) carcinoma samples.(EPS)Click here for additional data file.S3 FigViolin plots of overall percent agreement between CD8-positive and CD8-negative calls at the tumor (block) level when (i) using the original set of samples and resampling sections only (top), and (ii) when resampling both patients and then sections within patient (bottom). Scenario (i) captures technical reproducibility in this data set, while scenario (ii) attempts to capture variability in agreement calls in future samples of the same size. Treating the block-level mean as the gold standard "true" value of CD8 expression for that sample, using even just one slide (as opposed to averaging or taking the max of two slides) resulted in high agreement when applying a median (50th percentile) cut-off. Red points indicate a subsample of results over rounds of simulation.(EPS)Click here for additional data file.


Development of automatable processes for clustering proteins into functionally relevant groups is a critical hurdle as an increasing number of sequences are deposited into databases. Experimental function determination is exceptionally time-consuming and can’t keep pace with the identification of protein sequences. A tool, DASP (Deacon Active Site Profiler), was previously developed to identify protein sequences with active site similarity to a query set. Development of two iterative, automatable methods for clustering proteins into functionally relevant groups exposed algorithmic limitations to DASP.The accuracy and efficiency of DASP was significantly improved through six algorithmic enhancements implemented in two stages: DASP2 and DASP3. Validation demonstrated DASP3 provides greater score separation between true positives and false positives than earlier versions. In addition, DASP3 shows similar performance to previous versions in clustering protein structures into isofunctional groups , but DASP3 gathers and clusters protein sequences into isofunctional groups more efficiently than DASP and DASP2.DASP algorithmic enhancements resulted in improved efficiency and accuracy of identifying proteins that contain active site features similar to those of the query set. These enhancements provide incremental improvement in structure database searches and initial sequence database searches; however, the enhancements show significant improvement in iterative sequence searches, suggesting DASP3 is an appropriate tool for the iterative processes required for clustering proteins into isofunctional groups.The online version of this article (doi:10.1186/s12859-016-1295-z) contains supplementary material, which is available to authorized users. As protein sequence databases have exponentially increased in size , the demMany methods that group proteins by sequence or structural similarity are useful for inferring broad functional similarities to the degree that such similarities track with functional similarities. Resources such as PFAM , which iMore recently, methods such as GeMMA  and SCI-To overcome the limitations of full sequence similarity methods in tracking detailed molecular function, active site profiling was developed to compare proteins based on structural features at their functional sites . This meFor enzymes, sequence similarity networks have also recently been used to subdivide large protein superfamilies , 29 intoThe combination of active site profiling and protein clustering has shown notable promise in identifying detailed protein functional relationships from a single search of the sequence database , 27. HowBoth of these processes use iterative DASP searches of databases with each iteration building on the results of the previous search. This iterative searching illuminated limitations of the original DASP algorithm that only became apparent through search iterations. In this contribution, we describe the enhancements to the DASP algorithm to overcome these limitations and we demonstrate how the software modifications changed DASP scores and output results. The enhancements were built in two steps: three incremental enhancements to produce DASP2 and three more significant enhancements to produce DASP3. Validation of the significant algorithmic changes implemented into DASP3 is presented here, and their application to the iterative search processes demonstrates the improved quality of searches. , peroxiredoxin, radical SAM, and vicinal oxygen chelate (VOC)) in the SFLD  for both DASP/DASP2 and DASP3 is < 0.5 % at a generous threshold ≤1E-8 and < 0.01 % at a trusted threshold ≤1E-12. In this analysis, false positives are defined as proteins that are members of SFLD functional groups not included in the input profile. While the false positive discovery rate is slightly higher for DASP3 Fig. , right, The Two Level Iterative clustering Process (TuLIP), was recently developed to identify functionally relevant groups of protein structures using iterative clustering and DASP PDB searches (manuscript under review). In TuLIP, a protein cluster is defined as a functionally relevant group if the DASP PDB search returns only the proteins in the cluster at significant scores with no false positives. The process has demonstrated the ability to identify known isofunctional groups in multiple superfamilies (manuscript under review). However, major changes to the DASP algorithm could profoundly affect the groups identified in the TuLIP process. To analyze the impact of DASP modifications on TuLIP clustering, TuLIP was performed using both DASP2 and DASP3 on four superfamilies.Prior expert analysis separated the peroxiredoxin (Prx) superfamily into six subgroups . DASP waWhile DASP3 improves Prx subgroup identification over previous versions, additional SFLD superfamilies  showed minimal differences between the two versions. When DASP/DASP2 and DASP3 are used by TuLIP to cluster these three superfamilies into functionally relevant groups, 52 and 44 %, respectively, of TuLIP-identified groups correspond one-to-one with SFLD subgroups or families, a small difference that is not statistically significant . Notably, DASP3 identifies a large proportion of known Prx sequences in the appropriate groups; the average weighted F-measure at significance thresholds of ≤1E-8 and ≤1E-16 is 0.97 and 0.72, respectively.On average, the F-measure does not significantly differ between the DASP/DASP2 and DASP3 searches Fig. . HoweverAs only structurally characterized proteins are clustered by TuLIP, GenBank searches are necessary to identify protein sequences belonging to each TuLIP group. Therefore, the Multi-level Iterative Sequence Searching Technique (MISST) was developed to iteratively identify protein sequences with active site similarity to a given functionally relevant group and, further, to determine when such groups should be subdivided based on active site similarity (manuscript under review). MISST has demonstrated the ability to identify, cluster, and subdivide the Prx superfamily and other superfamilies using DASP2. Since MISST is a key method in our software arsenal and relies on iterative searching of the sequence database, it was relevant to compare the results of the MISST process using DASP/DASP2 and DASP3. Consequently, MISST was applied to the functionally relevant groups in the Prx superfamily.Three iterations of MISST were performed starting with the TuLIP groups identified by both DASP/DASP2 and DASP3 Fig. , as MISSUsing more stringent thresholds to reduce the presence of false positives : Platform independent, but paths are configured for LinuxProgramming language: JavaOther requirements: Java 1.5 or higherLicense: GPL 3.0Any restrictions to use by non-academics: None


Neoadjuvant chemo(radio)therapy followed by surgery is the standard of care for patients with locally advanced resectable esophageal adenocarcinoma (EAC). There is increasing evidence that drug resistance might be related to genomic heterogeneity. We investigated whether genomic tumor heterogeneity is different after cytotoxic chemotherapy and is associated with EAC patient survival. We used arrayCGH and a quantitative assessment of the whole genome DNA copy number aberration patterns (‘DNA copy number entropy’) to establish the level of genomic tumor heterogeneity in 80 EAC treated with neoadjuvant chemotherapy followed by surgery (CS group) or surgery alone (S group). The association between DNA copy number entropy, clinicopathological variables and survival was investigated.DNA copy number entropy was reduced after chemotherapy, even if there was no morphological evidence of response to therapy (p<0.001). Low DNA copy number entropy was associated with improved survival in the CS group (p=0.011) but not in the S group (p=0.396).Our results suggest that cytotoxic chemotherapy reduces DNA copy number entropy, which might be a more sensitive tumor response marker than changes in the morphological tumor phenotype. The use of DNA copy number entropy in clinical practice will require validation of our results in a prospective study. Pre-operative or peri-operative 5-fluorouracil/cisplatin based chemotherapy as well as pre-operative chemoradiotherapy followed by radical resection are the standard of care for patients with locally advanced, resectable esophageal adenocarcinoma (EAC) –3. HowevCytotoxic chemotherapy exerts one of the strongest selection pressures on cancer cells implying that chemotherapy treatment may favor the persistence of treatment resistant subpopulations .It has been suggested that drug resistance might be related to genomic tumor heterogeneity . High leSeveral studies have demonstrated the existence of genomic and/or phenotypic tumor heterogeneity in EAC –20. The Whole genome copy number profiling using array comparative genomic hybridization (aCGH) can provide a snapshot of the global DNA copy number aberration pattern. In this hypothesis-generating study, we used aCGH to quantify the degree of genomic tumor heterogeneity within a group of samples by estimating the DNA copy number entropy . This alThis study used DNA copy number entropy as a surrogate marker of genomic tumor heterogeneity. A representative DNA copy number profile with low DNA copy number entropy value and one with a high DNA copy number entropy value are shown in Figure EAC in the CS group had a significantly lower DNA copy number entropy value compared to EAC in the S group (median DNA copy number entropy (range) CS group: −0.524 (−1.801 to 1.289) versus S group: 0.321 (−1.411 to 1.315), p<0.001, Figure The comparison of the DNA copy number entropy values between the CS group and the S group stratified by chromosome showed that DNA copy number entropy values for chromosome 1 and chromosome 5 were significantly different. Median DNA copy number entropy (range) of chromosome 1 was −0.296 (−4.165 to 1.213) in the CS group compared to 0.483 (−3.070 to 1.645) in the S group, p=0.001. Similarly, the median DNA copy number entropy (range) of chromosome 5 was −0.271 (−3.800 to 1.255) in the CS group compared to 0.413 (−3.238 to 1.647) in the S group, p=0.03. However, related to the very high complexity of the aCGH profiles, we were not able to identify specific probes or genes neither on chromosome 1 nor on chromosome 5 which were significantly different between the treatment groups after applying rigorous multiple testing corrections. For all other chromosomes, the DNA copy number entropy values were not statistically significantly different between the CS and the S group .Although the median DNA copy number entropy values increased with increasing Mandard tumor regression grade category e.g. the highest DNA copy number entropy values were seen in EAC with no histological evidence of tumor regression (Mandard grade 5), this relationship was not statistically significant . The lack of statistical significance could be related to the relatively small sample size in the current study. Interestingly, the DNA copy number entropy values of EACs in the S group were significantly higher than the DNA copy number entropy values of EACs in the CS group with no histological evidence of tumor regression  (median (range) DNA copy number entropy of Mandard grade 5 EACs in the CS group: −0.292 (−1.801 to 0.685), median (range) DNA copy number entropy in the S group: 0.321 (−1.411 to 1.315), p< 0.001, Figure No association was found between depth of tumor invasion (pT/ypT), lymph node status (pN/ypN), grade of differentiation, lymphatic channel invasion, venous invasion or perineural invasion, and DNA copy number entropy neither when investigating these associations by treatment arm nor in the combined group .As a consequence of our case selection , the survival was not significantly different between the S and CS group. Thus, initial survival analyses were performed combining the two groups. Low DNA copy number entropy was significantly associated with longer cancer specific survival in the whole patient group . For Kaplan-Meier survival analysis, three equal sized patient groups were created based on the DNA copy number entropy values. As the survival curves of two of these groups overlapped substantially , these tCox regression analysis using continuous DNA copy number entropy values showed that DNA copy number entropy was significantly associated with cancer specific survival in the CS group  but not in the S group . For visualization of the Cox regression analysis results, Kaplan-Meier survival plots were created stratifying patients by using the median DNA copy number entropy per treatment group as cut-off. CS group patients with low DNA copy number entropy had a significantly better survival (median (range) survival time: 6.9 years (0 to 15.6 years)) compared to CS group patients with high DNA copy number entropy (0.9 years (0.7 to 0.97 years), p=0.011, Figure In order to assess whether the aCGH profiles and DNA copy number entropy of EAC of the current study are comparable to previously published EAC DNA copy number data, the frequency of DNA copy number aberrations and DNA copy number entropy of the S group EACs were compared to two recently published data sets , 23. VisEAC from the CS group had a median of 70% tumor cells/area ranging from 30 to 90% . EAC froThere have been a number of DNA copy number studies in esophageal adenocarcinoma (EAC) in the past, reporting different candidate genes or group of genes related to tumor progression or patient survival , 23–26. The frequency of DNA copy number aberrations (irrespective of the genes involved) has been related to survival in EAC in some but not all studies –25. The We found no relationship between DNA copy number entropy and any of the investigated clinicopathological data neither in the S group nor in the CS group. Importantly, there was also no statistically significant association between DNA copy number entropy and Mandard tumor regression grade of the primary tumor (only investigated in the CS group) or percentage of tumor/area (investigated in both groups). These results provide some confidence that the DNA copy number entropy is not simply a surrogate of some other pathological variable or known prognostic factor. Our findings are consistent with results reported in head and neck cancer where the variability of the mutant-allele fraction was used as marker of genomic tumor heterogeneity .et al [Our study showed that EACs after chemotherapy have DNA copy number profiles in which the aberrations were found more frequently at relatively similar locations, making them more ‘homogenous’ when measured by DNA copy number entropy compared to chemo-naïve EACs Figure . In contet al  reportedOur analyses comparing the DNA copy number entropy per chromosome between treatment groups showed that the difference in the DNA copy number entropy was strongly associated with the DNA copy number entropy in chromosome 1 and 5. The underlying mechanisms for this finding are currently unclear and warrant future studies. So far, there is no evidence from previous aCGH studies suggesting clinically relevant candidate genes on these particular chromosomes in EAC and we were unable to identify any individual significantly different probe or group of genes on these chromosomes in the current study.et al [Low DNA copy number entropy was only related to better outcome in EAC patients who had received chemotherapy prior to surgery. Mroz et al  reportedet al  reportedWe compared the aCGH profiles and the DNA copy number entropy of the surgery alone group with published data sets , 23. VisIn conclusion, this is the first study to quantify genomic tumor heterogeneity in esophageal adenocarcinoma, and to suggest that it might contribute to survival differences after chemotherapy.Our result requires validation in a larger independent cohort ideally comparing pre- and post-chemotherapy samples from the same tumor to directly measure the change in DNA copy number entropy induced by chemotherapy. The presence of genomic tumor heterogeneity, together with low frequencies of common aberrations across multiple cancers, makes the identification of predictive/prognostic biomarkers in EAC challenging, unless DNA copy number entropy itself can be used for this purpose. For the first time, we can show that cytotoxic chemotherapy appears to effect the tumor genotype (DNA copy number) in cases where the human eye cannot see any changes in the histological phenotype, suggesting that we might need to re-evaluate and potentially adapt the morphology based assessment criteria of primary tumor regression grading in particular in cases with a high tumor cell content per area.A better understanding of the mechanisms leading to genomic tumor heterogeneity is urgently needed before novel therapeutic strategies can be developed and outcome of EAC patients can finally be improved.The UK MRC OE02 trial recruited 802 patients with locally advanced esophageal cancer who were randomized to either two cycles of cisplatin/5-fluorouracil (5-FU) followed by surgery (CS group) or treatment by surgery alone (S group) between 1992 and 1998 [et al [The hematoxylin and eosin stained glass slides from all retrieved resection specimens and the original histopathology reports were reviewed to establish the histopathology data set used for analyses. Regression of the primary tumor was graded according to Mandard et al  centrallet al . DetailsThe tumor cell content per macrodissected tumor tissue area was estimated. As it had been shown previously that DNA copy number analyses from tumors with less than 30% tumor cells/area can be severely compromised , five cain situ synthesized oligonucleotides representing 169,793 unique chromosomal locations evenly distributed over the genome (spacing ~17 kb) and 4548 additional unique oligonucleotides, located at 238 of the Cancer Census genes (http://www.sanger.ac.uk/genetics/CGP/Census/).High-resolution array comparative genomic hybridization (aCGH) was performed using custom design 180K Agilent microarrays  containing 180,880 et al [Oligonucleotide positions were defined according to the NCBI36/hg18 assembly (March 2006). Labeling and hybridization were performed as described previously by Buffart et al . AgilentaCGH data were generated from 75 cases. The raw data underwent a series of pre-processing steps, which are detailed in Section S1 of the Supplementary file. The pre-processing was performed within the R statistical environment. After quantification, control spots  were removed from the data yielding 174,341 features. Both channels were background corrected by subtracting background median intensities from foreground median intensities to obtain an unbiased hybridization signal. Normalization, cellularity correction and segmentation were performed with the R-package CGHcall . The medDNA copy number profiles of the patients included in the current study were compared with two previously published DNA copy number data sets (Gene Expression Omnibus (GEO) database accession number: GSE36460 and GSE20154) , 23. AllNext, we quantified the degree of genomic tumor heterogeneity for each case by assessing the overall DNA copy number aberration pattern and estimating the DNA copy number entropy using the segmented data and the R-package sigaR   and >= 50% (high cellularity) samples in each treatment arm were projected on its first two principal components separately, for visual inspection of the difference in scatterness.The association between DNA copy number entropy and cancer specific survival was investigated using a Cox proportional hazards model. The potential prognostic value of the treatment, in addition to DNA copy number entropy, was investigated in a Cox proportional hazards model.The associations between DNA copy number entropy and tumor regression grade (CS group only), depth of invasion (pT/ypT), lymph node status (pN/ypN) and grade of differentiation were investigated using the test statistic implemented in the R-package sigaR. P-values <0.05 were considered statistically significant for single tests, and Benjamini-Hochberg corrected false discovery rates (FDR) <0.1 were considered statistically significant for multiple tests. Statistical analyses were performed using R, version 3.0.The study was approved by the London – South East ethics committee (REC reference: 07/H1102/111).


Myeloid sarcoma is an extramedullary (EM) manifestation  of acute myeloid leukemia (AML); it is assumed to be relatively uncommon and can be the only manifestation of leukemia relapse after allogenic stem cell transplantation . An EM sarcoma can manifest in any part of the body, although preferentially manifesting in immunological sanctuary sites as a single or multiple tumors. The development of myeloid sarcoma after allo-SCT is associated with certain cytogenetic abnormalities, developing of graft versus host disease (GVHD), and treatment with donor lymphocytes infusion (DLI). It is believed that posttransplant myeloid sarcomas develop because the EM sites evade immune surveillance. We present two patients with EM myeloid sarcoma in the breast and epipharynx, respectively, as the only manifestation of leukemia relapse. Both patients were treated with a combination of local and systemic therapy, with successfully longtime disease-free survival. Based on these two case reports, we give an updated review of the literature and discuss the pathogenesis, diagnosis, and treatment of EM sarcoma as the only manifestation of AML relapse after allo-SCT. There are no standard guidelines for the treatment of myeloid sarcomas in allotransplant recipients. In our opinion, the treatment of these patients needs to be individualized and should include local treatment  combined with systemic therapy . The treatment has to consider both the need for sufficient antileukemic efficiency versus the risk of severe complications due to cumulative toxicity. Myeloid sarcoma is a rare manifestation of AML and can appear concomitantly with, following or rarely antedating the onset of bone marrow leukemia . MS can NUP98 gene on chromosome 11. Medical termination was performed before she received conventional induction therapy with daunorubicin 50 mg/m2 once daily on days 1–3 and cytarabine 200 mg/m2 as daily continuous infusion on days 1–7, and she reached complete hematological remission after this single induction cycle. This treatment was followed by consolidation therapy with 4 cycles of high-dose cytarabine, each of these cycles consisting of cytarabine 3 g/m2 twice daily on days 1, 3, and 5.The patient was a 40-year-old Asian female diagnosed with AML during pregnancy . The bonp53 gene. The immunophenotypic features were similar as at initial diagnosis. New induction treatment was performed by idarubicin 12 mg/m2 once daily on days 1–3 and cytarabine 200 mg/m2 as daily continuous infusion on days 1–7, and again she reached complete hematological remission after one induction cycle. Then she was given further consolidation therapy with one cycle of amsakrin 150 mg/m2 once daily on days 1–5, etoposide 110 mg/m2 once daily on days 1–5, and cytarabine 200 mg/m2 as daily continuous infusion on days 1–5. After this, she proceeded to myeloablative conditioning (MAC) allo-SCT with a matched sibling donor. She showed no sign of GVHD at any time after the transplantation, and she achieved full donor chimerism.Relapsed disease was diagnosed 24 months after the first treatment was completed; at the time of relapse, she was pregnant in the 28th week and she was induced for labor in the 29th week. Cytogenetic analysis detected the original t translocation in 6 out of 14 metaphases, and additional t with a translocation between chromosome 12p11 and 17q11 was also detected together with loss of the derivative chromosome 17. The latter abnormality leads to the loss of genes on 17p including the 2 once daily on days 1–3 and cytarabine 200 mg/m2 as daily continuous infusion on days 1–7. Control PET examination after one induction cycle showed complete regression of fluorodeoxyglucose (FDG) uptake in the left breast. The patient denied further intensive chemotherapy and retransplantation. She therefore received consolidation treatment by radiation therapy 2 Gy × 15  against both breasts. In addition, she received three donor lymphocyte infusions (DLIs) in total 1.6 × 108 cells/kg; G-CSF-primed cells harvested at the time of stem cell harvesting were used for all three DLIs. After the last DLI, she presented with oral and skin manifestations consistent with GVHD and this diagnosis was confirmed with biopsy/histology. She has now been in complete remission without any signs of leukemia for 22 months after diagnosis of relapse as MS.She presented with a tumor in her left breast 62 months after the allo-SCT, and biopsy confirmed the diagnosis of myeloid sarcoma . ImmunopFLT3 or NPM1 genes (2 once daily on days 1–3 and cytarabine 200 mg/m2 as daily continuous infusion on days 1–7). However, he had persistent leukemic blasts in the bone marrow 16 days after start of this cycle; additional treatment with cytarabine and idarubicin  was started the next day. He now reached a complete hematological remission and received consolidation with another cycle of cytarabine plus idarubicin (5 + 2 regimen) and thereafter one cycle of high-dose cytarabine. The patient proceeded to allo-SCT with myeloablative conditioning based on busulfan plus cyclophosphamide with an HLA-matched sibling donor. 21 months after the transplantation, he presented with increased liver enzymes and histological changes in his oral cavity confirmed by biopsy to be chronic GVHD (cGVHD). Thirty-nine months after allo-SCT, he presented with symptoms from his left ear, and he was diagnosed with an epipharyngeal tumor; biopsies from this lesion demonstrated tumor of myeloid origin . After this treatment, he developed mucosal skin lesions in mouth consistent with cGVHD; for this reason, he never received DLI. MRI taken after completion of radiotherapy showed total regress of the tumor. He is still in complete remission 72 months after the diagnosis of relapse.This patient was a 34-year-old Caucasian male diagnosed with normal karyotype AML  without mutations in the M1 genes . With mud origin . The tumde novo MS, whereas soft tissues are more often involved in secondary MS [MS is a tumor of immature myeloid cells located at an extramedullary (EM) site; it can develop in any organ or site in the body but is more common at the immunological sanctuary sites of the testis, ovary, and central nervous system (CNS) , 3. Resundary MS , althougndary MS . Thus, bAn EM AML relapse will usually progress to involve other EM sites as well as the bone marrow within one year . The incThe best treatment of isolated EM relapse after allo-SCT is unknown , 11. PreIt is believed that the general immune-mediated antileukemic reactivity mediated by the general graft versus host reactivity that is associated with the occurrence of GVHD preferentially maintains bone marrow remission but does not prevent EM relapse . The occde novo and secondary MS with regard to treatment and prognosis [There are no established guidelines for the treatment of EM relapse after allo-SCT. The common practice is a combination of local and systemic treatment including intensive chemotherapy, local radiotherapy, DLI, and/or retransplantation , 9. Antirognosis , and trerognosis , 16.Treatment options for patients with EM relapse should be considered individually . Since rA possible treatment for isolated EM relapse is gemtuzumab/ozogamicin (GO), acting by depleting CD33-expressing leukemic cells and possible bolstering antileukemic immune reactivity , 19. TheEM posttransplant AML relapse may be more common than previously assumed, and its prognosis remains poor even though possibly slightly better than for combined EM and bone marrow relapse or bone marrow relapse alone. No guidelines for standard treatment of these patients are available, but a common practice is systemic chemotherapy or immunotherapy  combined with local radiotherapy. Cumulative toxicities due to previous chemotherapy and the risk of suppressing clinically relevant antileukemic immune reactivity have to be considered when the treatment of such patients is decided. Our two patients received intensive chemotherapy induction followed by consolidating radiotherapy, and only one of them received DLI; both patients are still alive without relapse. Future studies should focus on the development of diagnostic strategies for earlier detection of EM relapse and the identification of molecular mechanisms  behind EM homing of leukemic cells.


Post-translational modifications (PTMs) represent an important regulatory instrument that modulates structure, dynamics and function of proteins. The large number of PTM sites in the Hsp90 proteins that are scattered throughout different domains indicated that synchronization of multiple PTMs through a combinatorial code can be invoked as an important mechanism to orchestrate diverse chaperone functions and recognize multiple client proteins. In this study, we have combined structural and coevolutionary analysis with molecular simulations and perturbation response scanning analysis of the Hsp90 structures to characterize functional role of PTM sites in allosteric regulation. The results reveal a small group of conserved PTMs that act as global mediators of collective dynamics and allosteric communications in the Hsp90 structures, while the majority of flexible PTM sites serve as sensors and carriers of the allosteric structural changes. This study provides a comprehensive structural, dynamic and network analysis of PTM sites across Hsp90 proteins, identifying specific role of regulatory PTM hotspots in the allosteric mechanism of the Hsp90 cycle. We argue that plasticity of a combinatorial PTM code in the Hsp90 may be enacted through allosteric coupling between effector and sensor PTM residues, which would allow for timely response to structural requirements of multiple modified enzymes. According to these large-scale investigations, PTMs can regulate protein activity through diverse mechanisms, including modifications of binding sites and protein-protein interactions, protein localization, degradation, cleavage, and allosteric regulation of enzyme activity. Systematic functional analysis of 200,000 phosphorylation, acetylation, and ubiquitination sites from 11 eukaryotic species prioritized the functional relevance of PTMs in cross-regulatory events and protein-protein interactions by considering evolutionary conservation patterns of PTMs within domain families5. Diversity and sensitivity of PTM-mediated regulation is enabled not only by individual PTM sites and specific PTM types, but often through cooperative action and mutual interdependencies between multiple PTMs, which is often referred as functional PTM cross-talk8. Multiple PTMs can be linked through evolutionary and functional couplings that can be used to distinguish PTM-mediated regulatory hotspots and molecular switches of protein functions and allosteric interactions6. A comparative analysis of multiple PTM types in different eukaryotic species revealed correlated evolution of PTM pairs in proteins, showing that coevolving PTM pairs are not necessarily close in sequence space but can often enjoy structural proximity and physical interactions, forming regulatory centers in protein structures7. A proteome-wide survey of co-occurring phosphorylation pairs that tend to be modified together showed that these PTMs can be often functionally associated8. Using large experimental data sets, another study identified motifs enriched by pairs of known PTM sites, including three combinations of PTM types: phosphorylation-acetylation, phosphorylation-SUMOylation, and phosphorylation-phosphorylation9. A systematic characterization of functional cross-talk between PTM sites using 193 experimentally validated PTM pairs in 77 human proteins demonstrated that these pairs could exhibit proximity in both sequence and structure space, showing preferential colocalization for flexible and disordered regions10. Integration of acetylation, ubiquitination and phosphorylation datasets with protein interaction data emphasized a central role of phosphorylation in mediating of protein–protein interactions11. Among 12 different main PTM types and across 9 diverse species, phosphorylated proteins feature the broadest spectrum of physically interacting proteins in signaling networks12. MS-based proteomics studies revealed complexity of functional cross-talk between PTMs in protein families, suggesting that a combinatorial PTM code may be at play to enable additional layers of protein communication, biological regulation and redundancies in the cellular environment16.Significant biological insights in the functional roles of diverse PTM types in regulation of protein families and signaling networks have been obtained in recent years by utilizing systems-level quantitative analyses, including high-resolution mass spectrometry (MS) and systems biology approaches17. The majority of PTMs are typically localized in protein structural environments accessible to outside modifying enzymes, mostly in solvent-exposed and flexible regions18 and the accessibility criterion can be used to triage the proposed PTM sites19. Phosphorylation events are often accompanied by conformational switching of proteins that triggers significant changes in the accessibility of PTM sites, suggesting that these modifications of these functional residues can enact allosteric transformations in protein structures22. Computational analysis of phospho-proteome quantified structural preferences of PTM sites, showing that a significant amount of studied phosphorylation sites (24.6%) can reside in relatively inaccessible protein regions23. Phosphorylation and lysine acetylation sites tend to be enriched at the protein interfacial regions and have a significant impact on protein function by modulating the strength and specificity of physical binding interactions in protein networks25. A systematic analysis of PTM sites that can alter protein functions by promoting allosteric conformational changes suggested that allosteric PTMs can play an important role in plasticity of a combinatorial PTM code, allowing for precise regulatory control of multiple PTMs in the proteome context26.Structure-centric studies of PTMs in protein families showed that residues modified by more than one type of PTM can often correspond to more disordered regions than single PTM sites30. The Hsp90 chaperone operates as a homodimer and each monomer consists of three distinct domains: an N-terminal domain (Hsp90-NTD) that harbors the ATP binding site, a middle domain (Hsp90-MD), which is implicated in binding of client proteins, and a C-terminal domain (Hsp90-CTD) that is required for constitutive dimerization. Structural studies characterized main stages of the Hsp90-ATPase functional cycle associated with the ATP binding and hydrolysis, in which Hsp90 progresses from open apo and ADP-bound forms to a catalytically competent closed ATP-bound dimer30. The Hsp90 functions and interactions with client substrates can be regulated by cochaperones32 and through a diverse spectrum of PTMs, including phosphorylation, acetylation, S-nitrosylation, methylation, oxidation, ubiquitination, and SUMOylation34. Several phosphorylation sites in the Hsp90-NTD (T22 andY24 in yeast Hsp82) can alter progression of the ATPase cycle and modulate activation of protein kinase clients by weakening interactions with the kinase-specific cochaperone Cdc37 and impeding conformational transitions between functional states37. A quantitative analysis of phosphorylation sites in yeast Hsp82 revealed their functional role as molecular switches of conformational equilibrium and allosteric interactions as phosphorylation-mimicking chaperone variants in the Hsp82-MD regions  and Hsp82-CTD  featured the markedly reduced rates of ATP hydrolysis38. A greater number of phosphorylation sites were identified in the human Hsp90α and Hsp90β chaperones40. A systematic survey of PTM sites in molecular chaperones argued that these sites may have been selected by evolution for rapid and efficient regulation of diverse chaperone functions due to their integrating role in cellular protein networks41. Although decoding PTM patterns and linking them with specific regulatory mechanisms presents a daunting task, there are several lines of evidence suggesting that cochaperones and PTMs can exploit similar mechanisms to modulate chaperone function42. Recent evidence suggested that inhibition of client kinases that catalyze the vast majority of Hsp90 PTMs can act synergistically with Hsp90 inhibitors, providing a novel therapeutic strategy to enhance the efficacy of Hsp90 inhibitors in cancer cells44.Dissecting functional roles and couplings of PTMs in the family of the 90 kDa heat-shock (Hsp90) proteins is of fundamental and therapeutic importance as these abundant and evolutionary conserved molecular chaperones manage conformational development, maturation and folding for a wide array of protein client substrates, including protein kinases and transcription factors40. Despite recent progress in functional characterization of PTMs in protein systems, molecular mechanisms by which functionally important PTMs can exert control over allosteric regulation in the Hsp90 chaperones remain poorly understood and mostly qualitative in nature. In the current study, we have combined evolutionary analysis, all-atom and coarse-grained simulations of the Hsp90 proteins with the network analysis of residue interactions and perturbation response scanning (PRS) approach to probe allosteric mechanisms and quantify functional roles of PTM sites in allosteric regulation of the molecular chaperone. This study provides a comprehensive structural, dynamic and network analysis of PTM sites across Hsp90 proteins, identifying specific role of regulatory PTM hotspots in modulating of allosteric interactions and signal transmission in the Hsp90 structures. The results reveal conserved PTMs that act as central mediators and regulatory hotspots of allosteric signaling in the Hsp90 proteins, while the majority of PTM sites serve as sensors and transmitters of the allosteric signal in collectively moving Hasp90 regions. By combining PRS analysis of functional centers and network-based modeling of allosteric communication pathways, we determine key regulatory PTM sites in the Hsp90 chaperones can serve as gate-keepers and conformational switches of chaperone functions and interactions.The large number of PTM sites in the Hsp90 proteins that are scattered throughout all domains (sew Supplementary Tables http://www.phosphosite.org/) that contains over 330,000 non-redundant PTMs, with 95% of the sites obtained from mass spectrometry experiments3. We extracted all PTM sites in the Hsp90 genes that emerged from the experimental studies with at least two validated references. The experimentally validated Hsp90 PTM sites that are examined in this work included yeast Hsp82  profile generated using hidden Markov models in the Pfam database47. To analyze domain-based distribution of PTM sites in the Hsp90 proteins, we mapped KL conservation scores with the respective protein residues in the crystal structure of ATP-bound yeast Hsp82 (pdb id 2CG9)48 , as this region in all Hsp90 structures forms contacts with the equivalent segment of the opposing dimer. While the majority of PTM sites were localized in flexible regions accessible to modifying enzymes, a number of conserved PTM sites were partially buried, often occupying strategic positions near the inter-domain and dimerization interfaces 48 Fig. , the cry 49 Fig. , and cry 51 Fig. . In the  51 Fig. . In agre 51 Fig. , and theces Fig. .Figure 139. In particular, mutations of the Hsp82-NTD sites (T22 andY24) have a profound effect on the ATPase cycle by impeding conformational transitions and preventing formation of a catalytically competent closed dimer37. According to recent functional studies, phosphorylation of S379 position can perturb local structural environment of the catalytic site and weaken the inter-domain interactions between NTD and MD regions38. At the same time, mutations of other conserved PTM sites  are believed to exert their deleterious effects by interfering with the allosteric cross-talk between PTMs and compromising long-range allosteric communications in the Hsp82 dimer38. A significantly larger number of known PTM sites in the human Hsp90β provided more convincing statistics, showing that the vast majority of PTM residues belonged to highly variable positions  are spatially separated and occupy all three domains Fig. . Most ofons Fig. . Structuons Fig. .35, c-Src kinase (Y301)52, and pregnancy-upregulated nonubiquitous calmodulin kinase Pnck (S391 site)54. Interestingly, phosphorylation status of Y301 in the Hsp90β chaperone can elicit isoform specific binding to therapeutic agent geldamacyn (GA), as phosphomimetic mutations in this position considerably reduce inhibitor binding, while the respective mutations in Hsp90α (Y309E and Y309F) did not have a measurable effect on the binding affinity43. Several moderately conserved PTM sites  in the human Hsp90β  showed that changes in the acetylation state of PTM sites that are proximal to inter-domain interfaces can radically affect cochaperone binding and compromise maturation of client proteins40. While this site showed only a moderate sequence conservation, it is shared by yeast Hsp82 (K274) and Hsp90α (K294), indicating that functional importance and conservation of PTMs are not linked through a simple linear relationship. The conserved PTM positions in the Grp94 chaperone are exclusively lysine acetylation sites  that occupied the NTD and MD regions  included several important phosphorylation sites  and a number of lysine acetylation sites that populated the inter-domain regions Fig. . The hig90β Fig.  have a sons Fig. . SeveralHence, evolutionary and structural analyses suggested that functional PTM sites in the Hsp90 proteins tend to be conserved and often occupy strategic positions near the inter-domain interfaces Fig. . However57. The RSA values can be used as proxy for predicting intrinsic residue flexibility and the extent of conformational changes that may occur upon complex formation. According to this model, residues are considered to be completely solvent exposed if the ratio value exceeds 50% and to be buried if the ratio is less than 20%.Solvent accessibility and conformational flexibility are often strong indicators of PTM sites in proteins. However, conformational transformations in allosterically regulated systems can change structural environment and modulate the exposure and accessibility of the regulatory PTM sites. To characterize structural environment of PTM sites in the Hsp90 proteins, we evaluated relative solvent accessibility (RSA) of protein residues Fig.  and resi54. These regions are involved in coordinated structural changes that render the respective PTM sites become accessible to modifications by kinase clients. While structural changes can radically alter accessibility status for some PTM sites in the open and closed Grp94 structures, only moderate RSA differences were detected for conserved K410, K434, and K467 positions that retained their relatively low accessibility in both structural forms of Grp94 , which determines not only whether a residue is exposed or buried, but also quantifies the distance (depth) of a residue from the protein surface and from the closest bulk watertes Figs  and 3. Htes Figs . Accordites Figs . As expetes Figs . A genertes Figs . A compates Figs . Our ana63 of the Hsp90 structures. In these simulations, we explored and characterized conformational landscapes of ATP-bound yeast Hsp82 (pdb id 2CG9)48  method68 which is a matrix decomposition-free method that utilizes topological connectivity in protein structures to estimate rigidity and flexibility of Hsp90 residues. Using all-atom reconstructed conformations along DMD trajectories, we computed the ensemble-based average FRI profiles for the Hsp90 structures  belongs to a conserved SRE motif of the catalytic loop, which is involved in the nucleotide coordination and stabilization of the NTD-MD interactions. These results suggested that strategic structural position and stability of the conserved PTM sites in the NTD and NTD-MD regions may be associated with their unique regulatory roles. At the same time, we noticed that PTM sites in the CTD regions may form local clusters of highly mobile residues. In particular, a number of Hsp90β PTM sites  corresponded to local fluctuation peaks in the dynamics profile  simulations and coarse-grained discrete molecular dynamics (DMD))48 Fig. , ATP-bou 49 Fig. , and ATP 51 Fig. . We focures Fig.  and humares Fig.  were conion Fig. . The dynles Fig.  and coarles Fig. . A similles Fig.  and 5b. ile Fig.  and disp55. In the open Grp94 form, conserved PTM positions in the NTD regions  maintained considerable mobility, while another group of regulatory PTM sites  displayed a markedly reduced mobility and only moderate accessibility des Fig. . The maxdes Fig. . Hence, ons Fig. , which m72.A similar trend emerged from the analysis of the human Hsp90β Fig. . StrikinIn general, we found that moderately conserved PTM sites (a large fraction of PTMs) can serve as integrating nodes of collectively moving regions in global modes, while several highly conserved PTM positions  belong to stable hinge centers that coordinate execution of allosteric transitions in the Hsp90 structures. Based on these results, we suggested that functional cross-talk between PTM sites may be associated with their role in modulating collective motions and allosteric communications in the Hsp90 structures.We also explored the relationships between conformational dynamics, sequence conservation and residue coevolution in the Hsp90 protein family.46, we computed cumulative mutual information score (cMI) for each residue and the proximity mutual information score (pMI), which measures the mutual information shared by the residues in the structural proximity of a given residue. The important observation of coevolutionary analysis is that conserved PTM sites near regulatory hinge centers of the NTD-MD region are characterized by high pMI values, while moderately conserved and flexible PTM residues in the CTD regions can be distinguished by high cMI values  approachAs a result, these PTM sites can mediate coevolutionary network that confers a direct path for transmitting long-range signals between mobile regions. In this mechanism, local clusters of coevolving residues in the mobile CTD regions are enriched by PTM sites to control propagation of conformational changes and modulation of allosteric signaling in the Hsp90 dimers .75. This approach was successfully used in probing allosteric mechanisms in single protein domains and large multi-domain assemblies79. The average perturbation response maps are matrices in which the ijth element refers to the average response (displacement) of residue j to external perturbation at residue i. The average effect of the perturbed effector site i on all other residues i to influence dynamics changes in all other residues. In this model, the maxima of the effector profiles can be interpreted as allosteric hotspot residues that exert global control over propagation of allosteric communications to other protein residues. The sensor profile j to perturbations of all other residues and evaluates its ability to serve as a receiver (carrier) of allosteric signal. As a result, the maxima along the sensor profile can be attributed to residues that are involved in transmission of allosteric structural changes.We employed perturbation response scanning (PRS) method to quantify the role of PTM sites in allosteric signaling by probing the effect of each residue in the Hsp90 structures on all other residues in response to external perturbation. PRS formalism is rooted in the linear response theory to estimate residue response to external forces applied systematically to each residue in the protein system36. According to our results, these residues can exert both local and global effects on chaperone activity through their role as major effectors of signal transmission. Similar arguments could reconcile strong effects of phosphorylation-mimicking S379 variants on the rates of ATP hydrolysis38. A close proximity of S379 to the ATP binding site suggested that phosphorylation at this position may disrupt local structural environment in the catalytic loop and affect stability of the closed Hsp90 dimer38. Our results showed that S379 residue could also serve as a key mediator of long-range interaction governing signal transmission across the NTD-MD interface  were also singled out as potential controllers of allosteric signaling in the analysis of human Hsp90α 72. While many conserved PTM sites dominated the effector profile, less conserved PTM positions corresponded to the peaks of the sensor profile  are weighted based on the MD-derived residue-residue couplings and coevolutionary residue correlations. In this model, allosteric communications are determined by short inter-residue paths that transmit signals through dynamically correlated and coevolutionary-coupled nodes. We explored edge betweenness  in the global interaction network as a proxy for modeling of allosteric communication pathways. This parameter is defined as the ratio of all the shortest paths passing through a particular edge to the total number of shortest paths in the network. The central objective of this analysis was to quantify how allosteric signals may be transmitted between major effector and receiver centers localized in the NTD and CTD regions respectively.Using a graph-based representation of protein structures80. These findings may provide an additional insight in rationalizing deleterious mutational effects of these residues on the ATPase activity as perturbations in these regulatory control points may reduce the fidelity and efficiency of allosteric signaling in the Hsp82 dimer. Based on atomistic models of signaling paths in the Hsp82 dimer, we argue that a cross-talk between effector PTM sites  and sensor PTM sites  can be instrumental in modulation of allosteric signaling and ATPase activity. In this mechanism, single control points T22, T24, S379, and S485 can act as regulatory switches of conformational equilibrium and client interactions during the Hsp90-ATPase cycle.Analysis of high centrality bridges in the yeast Hsp82 revealed a number of mediating bridges that may be important for long-range signal propagation Fig. . We obse39. The critical role of this PTM site in signal propagation may explain why mutations in this position may divert the progression of the Hsp90 cycle and impair kinase client binding88.Structural models of communication paths in the human Hsp90β connecting major effector and sensor sites also revealed a considerable involvement of phosphorylation and lysine acetylation sites Fig. . Our fin26. By reconstructing the network of short paths transducing conformational information in the Hsp90 proteins, we suggest that allosteric coupling between PTMs could provide additional layers for regulation of chaperone activity and binding of client proteins.A communication map in the closed Grp94 dimer similarly indicated that PTM sites can be involved in mediating long-range signaling Fig. . Alloste7. Another study suggested that coevolutionary dependencies between some PTM sites may bias their structural proximity, masking a more global statistical tendency of all PTMs to be spatially separated and allow for simultaneous access to different sites89. By examining the interplay between coevolution, dynamics and allosteric communications in the Hsp90 structures, this study provided new insights into mechanisms underlying functional coupling and cross-talk between PTM sites. We determined that PTM sites occupy critical positions in slow modes, where a small fraction of conserved PTMs form spatially separated regulatory hinge centers, while the majority of coevolving flexible PTMs serve as integral nodes and form local clusters in cooperatively moving regions. These findings were further substantiated in the PRS analysis of allosteric residue responses to external perturbations. By employing a battery of complementary dynamic and network-based approaches, we presented consistent evidence that a small group of conserved PTM hotspots can play an important role in orchestrating allosteric signaling in the Hsp90 proteins, while less conserved and more flexible PTMs act as main transmitters of conformational changes. According to our results, functional cross-talk between PTM sites may be determined by their respective roles as effectors and sensors of allosteric signaling in the Hsp90 structures. The complementary roles of PTMs as effectors and sensors of allosteric signaling suggested how these sites may become involved either in positive or negative cross-talk91. In a positive cross-talk, a particular PTM serves as a signal for the addition or removal of a second PTM, while a negative crosstalk is often defined as direct competition between PTM sites where one modification masks the recognition site for a second PTM. We argue that plasticity of a combinatorial PTM core in the chaperone may be enacted through coupling between effector and sensor PTM sites, allowing for regulatory switching and rapid responses to structural requirements of multiple modified enzymes. The proposed computational framework that links dynamics and allosteric responses in multi-domain chaperone systems with diversity and functions of PTM sites may be useful in developing therapeutic strategies for designing robust combinations of targeted and allosteric inhibitors of chaperones and oncogenic kinase clients.Previous studies reported that cross-talk events preferentially occur among nearby PTM sites and cross-talking pairs tended to coevolve48 48 Fig. , the cry 49 Fig. , and cry 51 Fig. . All str63 to simulate Hsp90 structures  simulationsres Fig. . In the 86. MI is a nonlinear statistic that measures the information between two random and discrete variables. Given that any two positions in the MSA can be considered random variables x and y, the MI between is these two positions are given by the relationship:Analysis of coevolving residues was carried out using mutual information (MI) between two positions in the multiple sequence alignment (MSA), which reflects the extent to which knowing the amino acid at one position can predict the amino acid identity at the other position. MI was calculated between pairs of columns in the MSA using MISTIC approachi and amino acid b at position j of the same sequence. P(ai) is the frequency of amino acid a occurring at position i and P(bj) is the frequency of amino acid b at position j. The amino acid frequency pair i and j respectively. N is the total number of sequences in the sequence alignment. MSA were obtained from Pfam47, a database of protein families that includes their annotations and MSA information generated using hidden Markov models. The seed alignments of the HATPase_c family (PF02518) and Hsp90 family (PF00183) were used as the curated alignment which contains representative sequences of the chaperone family, from which a profile hidden Markov model (HMM) is generated using the HMMER3 program (http://hmmer.janelia.org/). Each profile is then searched against a primary sequence database based on UniProtKB to create the full MSA profile. The criteria parameters for generating a MSA are the E-value and the number of columns in the multiple-sequence alignment for which sufficient sequences can be found to infer evolutionary couplings. Based on these criteria, for sequences in the dataset, an E-value of 10−2 and a column-inclusion threshold of 80% were used in the MSA generation. All sequences in the full MSA score above curated thresholds are included in the full alignments. The Kullback-Leibler (KL) divergence score 86 using a combined MSA profile generated in the Pfam database47 for the HATPase_c family,  and the Hsp90 family . The KL parameter measures the population diversity of residues at a single MSA position and takes into account biochemical environment by considering frequency of mutations at each position with respect to the background amino acid frequencies calculated from the MSA. For each column of the MSA, the KL conservation is calculated according to the following formula:P(i) is the frequency of amino acid i in that position and Q(i) is the background frequency of the amino acid in nature calculated using an amino acids background frequency distribution. In the coevolutionary analysis, we computed the following parameters: a cumulative mutual information score 86.Here, 46:75 is based on the linear response theory and allows to evaluate residue displacements in response to external forces. In this approach, it is assumed that the 3N × 3N Hessian matrix, N × N PRS matrix. The second derivatives matrix α atoms and the deviation of each residue from an average structure was calculated by 78. The displacement changes, 3N-dimensional vector describing the linear response of the protein and deformation of all the residues. Using the residue displacements upon multiple external force perturbations, we compute the magnitude of the response of residue k as ikth element of the N × N PRS matrix78. The average perturbation response maps of the protein are matrices in which the ijth element refers to the average response (displacement) of residue Perturbation Response Scanning (PRS) approachi on all other residues is computed by averaging over all sensors (receivers) residues jth column of the PRS matrix describes the sensitivity profile of sensor residue j to serve as a receiver (or transmitter) of dynamic changes in the system. Accordingly, the maxima along the sensor profile correspond to functional residues in cooperatively moving regions involved in execution of allosteric structural changes.The average effect of the perturbed effector site 83 were outlined in our previous studies of the Hsp90 and Hsp70 chaperones95. The edges in the residue interaction network are weighted based on dynamic residue correlations couplings obtained from MD simulations84 and coevolutionary mutual information87. In this model, weight 87:A graph-based model of protein structure considers residues as network nodes while inter-residue edges represent residue interactions. The details of graph construction using residue i and j is calculated from the corresponding generalized correlation coefficient between these nodes104. The networks edges were constructed based on the generalized correlations between all residues obtained from multiple simulations. Network edges were weighted for residue pairs with 105. The ensemble of shortest paths is determined from matrix of communication distances by the Floyd-Warshall algorithm106 that compares all possible paths between each pair of residue nodes.The edge lengths in the network are thus obtained using the generalized correlation coefficients 107.At the first step, the distance between connected residues was considered to be one, and the shortest path was identified as the path in which the two distant residues were connected by the smallest number of intermediate residues. Network graph calculations were performed using the python package NetworkXAll data generated or analyzed during this study are included in this published article (and its Supplementary Information files).Supplementary Information


Retinoic acid (RA) is intrinsically linked to neurodevelopment and has been implicated in schizophrenia (SZ). This is supported by preliminary trials of a retinoid receptor agonist, Bexarotene, as an adjuvant and the association of five common variants in proximity to members of this pathway at genome wide significance. In addition to these high frequency variants with small effect size, we suspect that this pathway is also affected by rare variants with much higher impact. We aimed to examine the burden of variants in retinoid loci in schizophrenia along with its potential consequences for clinical practice.Whole genome sequencing was performed on SZ cases (N=331) and non-psychiatric controls (N=167). Cases were further clustered by cognitive measures to derive the cognitive deficit  and cognitively spared  subtypes. Disease and subtype associated genomic variation was then analysed in a panel of 129 genes selected for involvement in RA biology (Molecular Signatures Database). Rare variation was aggregated at the gene level using the optimal unified sequence kernel association test (SKAT-O). Clinical metadata was further examined for each case with a rare putative high impact loss of function variant in a RA panel gene predicted using SnpEff. The rare variant burden on target genes of RA receptor binding in SZ was investigated by logistic regression of variants mapped to consensus 5 base pair spaced direct repeat (DR5) retinoic acid response element (RARE) motifs.Gene level rare variant association uncovered suggestive associations with SZ (P < 0.01) for three retinoid genes – RBP3, ADH1C and RPE65. In addition, a stronger signal was detected overall for CD cases implicating four additional genes including the RA receptors RARB (P = 1.1 x 10–3) and RARG (P = 9.2 x 10–3). SZ patients with a rare high impact genotype predicted in a RA panel gene were more likely to have serious symptomology as defined by a global assessment of functioning (GAF) score below 50, P = 7.1 x 10–3 (Two-Tailed Fisher’s Exact Test). We also found evidence of an increased burden of rare variants within predicted DR5-RARE in SZ , however, there was no significant difference between the cognitive subtypes .Our findings suggest that RA mediated control of gene expression is heterogeneously disrupted in SZ by rare variants in DR5-RARE motifs. Strong signals in the context of our sample size further support the possibility of enrichment of rare loci in genes involved with RA biology, particularly in CD cases with impaired cognition. Moreover, we identified a subset of patients with likely high effect size genotypes in the RA pathway. Future work will examine whether these high-risk patients would benefit from retinoid based pharmacological intervention.


Epidermal growth factor receptor (EGFR) mutation-driven lung cancer is a rare occurrence in patients with Li-Fraumeni syndrome (LFS) characterized by germline mutations in the tumor protein 53 (TP53) gene. Here we describe a case of primary EGFR mutation-driven lung adenocarcinoma in a young woman with LFS. There is only one other reported case with such presentation. We review the interactions between the TP53 gene and EGFR pathways facilitating lung carcinogenesis. We also review other cases with similar presentations described in the literature and the response to tyrosine kinase inhibitors (TKI) in this rare patient population. Oncogenic driver mutations in lung cancer vary depending on smoking exposure, gender, and pathologic stage of the tumor. Somatic mutations in tumor protein 53 (TP53) are associated with smoking exposure and advanced disease stage, whereas epidermal growth factor receptor (EGFR) driver mutations are common in women and never smokers . Li-FrauA 28-year-old woman was screened for LFS after her 10-year-old daughter tested positive for germline TP53 gene mutation while undergoing evaluation for newly diagnosed sarcoma. She was found to carry familial heterozygous missense TP53 gene mutation in exon 7 causing nucleotide change c.733G>A with corresponding amino acid change p.G245S in the gene protein. Her two other children from the same partner, aged fourteen and four years, also carried the same mutation. Her partner did not carry the mutation and she had no family history of cancer.Hence she was enrolled in the high-risk cancer screening program, eighteen months later, she presented with a cough with white sputum and upper back pain. Symptoms did not improve with the course of antibiotics, therefore, she underwent further evaluation. Computed tomography (CT) scan of the chest  to erlotinib. It was treated with the periodic use of topical corticosteroids, topical urea, and two-week courses of doxycycline 100 mg capsules twice daily. Besides cutaneous toxicity, she had no other significant adverse effects from erlotinib. Follow up CT scan six months later showed (Figure Twelve months later she complained of unremitting left hip pain causing her to limp. CT scan of the left hip (Figure TP53 gene, also named the guardian of the genome, is the most important tumor suppressor gene encoding p53 transcription factor. Genotoxic stress causes a rise in p53 levels which activates downstream genes for cell cycle arrest, cell repair, and apoptosis. In the absence of normal TP53 protein, DNA damaged cells escape DNA repair or apoptosis, therefore malignant transformation is made possible. The rare LFS is characterized by predisposition to a wide spectrum of malignant conditions. About 70% of families with the syndrome carry autosomal dominant TP53 germline variants [TP53 gene is located on chromosome 17p13.1 and comprises fourteen exons of which ten are in the coding sequence of the 393 amino acids containing protein, one in the non coding exon, and remaining three are alternate exons. It transcribes at least eight different mRNAs and twelve protein isoforms, individual functions of which are still being deciphered. Missense mutations in the DNA binding domain of the protein are the most common alterations in LFS patients followed by nonsense and other mutational subtypes . GermlinEGFR is a transmembrane protein that has multiple ligands including epidermal growth factor and transforming growth factor-α. Ligand binding to EGFR causes an increase in intracellular tyrosine kinase activity and activation of multiple intracellular signaling pathways that promote cellular proliferation . Wild-tyThe patient described in our report carried germline TP53 missense mutation with dominant negative effect and developed primary EGFR mutant lung cancer. On literature review, there are two other described cases of primary EGFR mutant cancer in a patient with LFS . There aOn the contrary, retrospective studies have reported a negative prognostic value of concurrent somatic TP53 and EGFR mutation and data suggests a poor response to TKI in such patients . FurtherIn summary, our case highlights the cross talk between TP53 and EGFR in lung tumorigenesis. With increasing number of cases reporting concurrence of EGFR and germline TP53 mutations, it is prudent for treating oncologist to consider LFS when encountering lung cancer in young patients who are never smokers. It appears that EGFR targeted therapy is effective in such patients, however, long-term follow up is needed to determine if concurrent TP53 mutations confer a poor prognosis.