Results from the UNITED study: a multicenter study validating the prognostic effect of the tumor-stroma ratio in colon cancer.

BACKGROUND: The TNM (tumor-node-metastasis) Evaluation Committee of Union for International Cancer Control (UICC) and College of American Pathologists (CAP) recommended to prospectively validate the cost-effective and robust tumor-stroma ratio (TSR) as an independent prognostic parameter, since high intratumor stromal percentages have previously predicted poor patient-related outcomes. PATIENTS AND METHODS: The 'Uniform Noting for International application of Tumor-stroma ratio as Easy Diagnostic tool' (UNITED) study enrolled patients in 27 participating centers in 12 countries worldwide. The TSR, categorized as stroma-high (>50%) or stroma-low (≤50%), was scored through standardized microscopic assessment by certified pathologists, and effect on disease-free survival (DFS) was evaluated with 3-year median follow-up. Secondary endpoints were benefit assessment of adjuvant chemotherapy (ACT) and overall survival (OS). RESULTS: A total of 1537 patients were included, with 1388 eligible stage II/III patients curatively operated between 2015 and 2021. DFS was significantly shorter in stroma-high (n = 428) than in stroma-low patients (n = 960) (3-year rates 70% versus 83%; P < 0.001). In multivariate analysis, TSR remained an independent prognosticator for DFS (P < 0.001, hazard ratio 1.49, 95% confidence interval 1.17-1.90). As secondary outcome, DFS was also worse in stage II and III stroma-high patients despite adjuvant treatment (3-year rates stage II 73% versus 92% and stage III 66% versus 80%; P = 0.008 and P = 0.011, respectively). In stage II patients not receiving ACT (n = 322), the TSR outperformed the American Society of Clinical Oncology (ASCO) criteria in identifying patients at risk of events (event rate 21% versus 9%), with a higher discriminatory 3-year DFS rate (stroma-high 80% versus ASCO high risk 91%). A trend toward worse 5-year OS in stroma-high was noticeable (74% versus 83% stroma-low; P = 0.102). CONCLUSION: The multicenter UNITED study unequivocally validates the TSR as an independent prognosticator, confirming worse outcomes in stroma-high patients. The TSR improved current selection criteria for patients at risk of events, and stroma-high patients potentially experienced chemotherapy resistance. TSR implementation in pathology diagnostics and international guidelines is highly recommended as aid in personalized treatment.

Self-Supervised Learning Reveals Clinically Relevant Histomorphological Patterns for Therapeutic Strategies in Colon Cancer.

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-and-eosin-stained whole-slide images (WSIs). We trained an SSL Barlow Twins-encoder on 435 TCGA colon adenocarcinoma WSIs to extract features from small image patches. Leiden community detection then grouped tiles into histomorphological phenotype clusters (HPCs). HPC reproducibility and predictive ability for overall survival was confirmed in an independent clinical trial cohort (N=1213 WSIs). This unbiased atlas resulted in 47 HPCs displaying unique and sharing clinically significant histomorphological traits, highlighting tissue type, quantity, and architecture, especially in the context of tumor stroma. Through in-depth analysis of these HPCs, including immune landscape and gene set enrichment analysis, and association to clinical outcomes, we shed light on the factors influencing survival and responses to treatments like standard adjuvant chemotherapy and experimental therapies. Further exploration of HPCs may unveil new insights and aid decision-making and personalized treatments for colon cancer patients.

Clonal Relationship and Mutation Analysis in Lymphoplasmacytic Lymphoma/Waldenström Macroglobulinemia Associated With Diffuse Large B-cell Lymphoma.

Patients with lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM) occasionally develop diffuse large B-cell lymphoma (DLBCL). This mostly results from LPL/WM transformation, although clonally unrelated DLBCL can also arise. LPL/WM is characterized by activating MYD88L265P (>95%) and CXCR4 mutations (~30%), but the genetic drivers of transformation remain to be identified. Here, in thirteen LPL/WM patients who developed DLBCL, the clonal relationship of LPL and DLBCL together with mutations contributing to transformation were investigated. In 2 LPL/WM patients (15%), high-throughput sequencing of immunoglobulin gene rearrangements showed evidence of >1 clonal B-cell population in LPL tissue biopsies. In the majority of LPL/WM patients, DLBCL presentations were clonally related to the dominant clone in LPL, providing evidence of transformation. However, in 3 patients (23%), DLBCL was clonally unrelated to the major malignant B-cell clone in LPL, of which 2 patients developed de novo DLBCL. In this study cohort, LPL displayed MYD88L265P mutation in 8 out of eleven patients analyzed (73%), while CXCR4 mutations were observed in 6 cases (55%). MYD88WT LPL biopsies present in 3 patients (27%) were characterized by CD79B and TNFAIP3 mutations. Upon transformation, DLBCL acquired novel mutations targeting BTG1, BTG2, CD79B, CARD11, TP53, and PIM1. Together, we demonstrate variable clonal B-cell dynamics in LPL/WM patients developing DLBCL, and the occurrence of clonally unrelated DLBCL in about one-quarter of LPL/WM patients. Moreover, we identified commonly mutated genes upon DLBCL transformation, which together with preserved mutations already present in LPL characterize the mutational landscape of DLBCL occurrences in LPL/WM patients.

Consensus molecular subtype transition during progression of colorectal cancer.

The consensus molecular subtype (CMS) classification divides colorectal cancer (CRC) into four distinct subtypes based on RNA expression profiles. The biological differences between CMSs are already present in CRC precursor lesions, but not all CMSs pose the same risk of malignant transformation. To fully understand the path to malignant transformation and to determine whether CMS is a fixed entity during progression, genomic and transcriptomic data from two regions of the same CRC lesion were compared: the precursor region and the carcinoma region. In total, 24 patients who underwent endoscopic removal of T1-2 CRC were included. Regions were subtyped for CMS and DNA mutation analysis was performed. Additionally, a set of 85 benign adenomas was CMS-subtyped. This analysis revealed that almost all benign adenomas were classified as CMS3 (91.8%). In contrast, CMS2 was the most prevalent subtype in precursor regions (66.7%), followed by CMS3 (29.2%). CMS4 was absent in precursor lesions and originated at the carcinoma stage. Importantly, CMS switching occurred in a substantial number of cases and almost all (six out of seven) CMS3 precursor regions showed a shift to a different subtype in the carcinoma part of the lesion, which in four cases was classified as CMS4. In conclusion, our data indicate that CMS3 is related to a more indolent type of precursor lesion that less likely progresses to CRC and when this occurs, it is often associated with a subtype change that includes the more aggressive mesenchymal CMS4. In contrast, an acquired CMS2 signature appeared to be rather fixed during early CRC development. Combined, our data show that subtype changes occur during progression and that CMS3 switching is related to changes in the genomic background through acquisition of a novel driver mutation (TP53) or selective expansion of a clone, but also occurred independently of such genetic changes. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tumor-Infiltrating Normal B Cells Revealed by Immunoglobulin Repertoire Clonotype Analysis Are Highly Prognostic and Crucial for Antitumor Immune Responses in DLBCL.

PURPOSE: Tumor-infiltrating B lymphocytes (TIL-B) have demonstrated prognostic and predictive significance in solid cancers. In this study, we aimed to distinguish TIL-Bs from malignant B-cells in diffuse large B-cell lymphoma (DLBCL) and determine the clinical and biological significance. EXPERIMENTAL DESIGN: A total of 269 patients with de novo DLBCL from the International DLBCL R-CHOP Consortium Program were studied. Ultra-deep sequencing of the immunoglobulin genes was performed to determine B-cell clonotypes. The frequencies and numbers of TIL-B clonotypes in individual repertoires were correlated with patient survival, gene expression profiling (GEP) data, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex IHC at single-cell resolution. RESULTS: TIL-B abundance, evaluated by frequencies of normal B-cell clonotypes in the immunoglobulin repertoires, remarkably showed positive associations with significantly better survival of patients in our sequenced cohorts. DLBCLs with high versus low TIL-B abundance displayed distinct GEP signatures, increased pre-memory B-cell state and naïve CD4 T-cell state fractions, and higher CD4+ T-cell infiltration. TIL-B frequency, as a new biomarker in DLBCL, outperformed the germinal center (GC) B-cell-like/activated B-cell-like classification and TIL-T frequency. The identified TIL-B-high GEP signature, including genes upregulated during T-dependent B-cell activation and those highly expressed in normal GC B cells and T cells, showed significant favorable prognostic effects in several external validation cohorts. CONCLUSIONS: TIL-B frequency is a significant prognostic factor in DLBCL and plays a crucial role in antitumor immune responses. This study provides novel insights into the prognostic determinants in DLBCL and TIL-B functions with important therapeutic implications.

A significant proportion of classic Hodgkin lymphoma recurrences represents clonally unrelated second primary lymphoma.

Despite high cure rates in classic Hodgkin lymphoma (cHL), relapses are observed. Whether relapsed cHL represents second primary lymphoma or an underlying T-cell lymphoma (TCL) mimicking cHL is underinvestigated. To analyze the nature of cHL recurrences, in-depth clonality testing of immunoglobulin (Ig) and T-cell receptor (TCR) rearrangements was performed in paired cHL diagnoses and recurrences among 60 patients, supported by targeted mutation analysis of lymphoma-associated genes. Clonal Ig rearrangements were detected by next-generation sequencing (NGS) in 69 of 120 (58%) diagnoses and recurrence samples. The clonal relationship could be established in 34 cases, identifying clonally related relapsed cHL in 24 of 34 patients (71%). Clonally unrelated cHL was observed in 10 of 34 patients (29%) as determined by IG-NGS clonality assessment and confirmed by the identification of predominantly mutually exclusive gene mutations in the paired cHL samples. In recurrences of >2 years, ∼60% of patients with cHL for whom the clonal relationship could be established showed a second primary cHL. Clonal TCR gene rearrangements were identified in 14 of 125 samples (11%), and TCL-associated gene mutations were detected in 7 of 14 samples. Retrospective pathology review with integration of the molecular findings were consistent with an underlying TCL in 5 patients aged >50 years. This study shows that cHL recurrences, especially after 2 years, sometimes represent a new primary cHL or TCL mimicking cHL, as uncovered by NGS-based Ig/TCR clonality testing and gene mutation analysis. Given the significant therapeutic consequences, molecular testing of a presumed relapse in cHL is crucial for subsequent appropriate treatment strategies adapted to the specific lymphoma presentation.

Detection of Second Primary Lymphoma in Late Diffuse Large B-cell Lymphoma Recurrences.

Approximately one-third of patients with diffuse large B-cell lymphoma (DLBCL) relapse and often require salvage chemotherapy followed by autologous stem cell transplantation. In most cases, the clonal relationship between the first diagnosis and subsequent relapse is not assessed, thereby potentially missing the identification of second primary lymphoma. In this study, the clonal relationship of 59 paired DLBCL diagnoses and recurrences was established by next-generation sequencing-based detection of immunoglobulin gene rearrangements. Among 50 patients with interpretable results, 43 patients (86%) developed clonally related relapsed disease. This was observed in 100% of early recurrences (<2 years), 80% of the recurrences with an interval between 2 and 5 years, and 73% of late recurrences (≥5 years). On the other hand, 7 (14%) out of 50 patients displayed different dominant clonotypes in primary DLBCL and clinical recurrences, confirming the occurrence of second primary DLBCL; 37% of DLBCL recurrences that occurred ≥4 years after diagnosis were shown to be second primary lymphomas. The clonally unrelated cases were Epstein-Barr virus positive in 43% of the cases, whereas this was only 5% in the relapsed DLBCL cases. In conclusion, next-generation sequencing-based clonality testing in late recurrences should be considered in routine diagnostics to distinguish relapse from second primary lymphoma, as this latter group of patients with DLBCL may benefit from less-intensive treatment strategies.

Deep learning based tumor-stroma ratio scoring in colon cancer correlates with microscopic assessment.

Background: The amount of stroma within the primary tumor is a prognostic parameter for colon cancer patients. This phenomenon can be assessed using the tumor-stroma ratio (TSR), which classifies tumors in stroma-low (≤50% stroma) and stroma-high (>50% stroma). Although the reproducibility for TSR determination is good, improvement might be expected from automation. The aim of this study was to investigate whether the scoring of the TSR in a semi- and fully automated method using deep learning algorithms is feasible. Methods: A series of 75 colon cancer slides were selected from a trial series of the UNITED study. For the standard determination of the TSR, 3 observers scored the histological slides. Next, the slides were digitized, color normalized, and the stroma percentages were scored using semi- and fully automated deep learning algorithms. Correlations were determined using intraclass correlation coefficients (ICCs) and Spearman rank correlations. Results: 37 (49%) cases were classified as stroma-low and 38 (51%) as stroma-high by visual estimation. A high level of concordance between the 3 observers was reached, with ICCs of 0.91, 0.89, and 0.94 (all P < .001). Between visual and semi-automated assessment the ICC was 0.78 (95% CI 0.23-0.91, P-value 0.005), with a Spearman correlation of 0.88 (P < .001). Spearman correlation coefficients above 0.70 (N=3) were observed for visual estimation versus the fully automated scoring procedures. Conclusion: Good correlations were observed between standard visual TSR determination and semi- and fully automated TSR scores. At this point, visual examination has the highest observer agreement, but semi-automated scoring could be helpful to support pathologists.

Correlation of Immunological and Histopathological Features with Gene Expression-Based Classifiers in Colon Cancer Patients.

The purpose of this study was to evaluate the association between four distinct histopathological features: (1) tumor infiltrating lymphocytes, (2) mucinous differentiation, (3) tumor-stroma ratio, plus (4) tumor budding and two gene expression-based classifiers­(1) consensus molecular subtypes (CMS) plus (2) colorectal cancer intrinsic subtypes (CRIS). All four histopathological features were retrospectively scored on hematoxylin and eosin sections of the most invasive part of the primary tumor in 218 stage II and III colon cancer patients from two independent cohorts (AMC-AJCC-90 and AC-ICAM). RNA-based CMS and CRIS assignments were independently obtained for all patients. Contingency tables were constructed and a χ2 test was used to test for statistical significance. Odds ratios with 95% confidence intervals were calculated. The presence of tumor infiltrating lymphocytes and a mucinous phenotype (>50% mucinous surface area) were strongly correlated with CMS1 (p < 0.001 and p = 0.008) and CRIS-A (p = 0.006 and p < 0.001). The presence of mucus (≥ 10%) was associated with CMS3: mucus was present in 64.1% of all CMS3 tumors (p < 0.001). Although a clear association between tumor-stroma ratio and CMS4 was established in this study (p = 0.006), still 32 out of 61 (52.5%) CMS4 tumors were scored as stroma-low, indicating that CMS4 tumors cannot be identified solely based on stromal content. Higher budding counts were seen in CMS4 and CRIS-B tumors (p = 0.045 and p = 0.046). No other associations of the measured parameters were seen for any of the other CRIS subtypes. Our analysis revealed clear associations between histopathologic features and CMS or CRIS subtypes. However, identification of distinct molecular subtypes solely based on histopathology proved to be infeasible. Combining both molecular and morphologic features could potentially improve patient stratification.

Accurate staging of non-metastatic colon cancer with CT: the importance of training and practice for experienced radiologists and analysis of incorrectly staged cases.

PURPOSE: To investigate whether locoregional staging of colon cancer by experienced radiologists can be improved by training and feedback to minimize the risk of over-staging into the context of patient selection for neoadjuvant therapy and to identify potential pitfalls of CT staging by characterizing pathologic traits of tumors that remain challenging for radiologists. METHODS: Forty-five cases of stage I-III colon cancer were included in this retrospective study. Five experienced radiologists evaluated the CTs; 5 baseline scans followed by 4 sequential batches of 10 scans. All radiologists were trained after baseline scoring and 2 radiologists received feedback. The learning curve, diagnostic performance, reader confidence, and reading time were evaluated with pathologic staging as reference. Pathology reports and H&E slides of challenging cases were reviewed to identify potential pitfalls. RESULTS: Diagnostic performance in distinguishing T1-2 vs. T3-4 improved significantly after training and with increasing number of reviewed cases. Inaccurate staging was more frequently related to under-staging rather than over-staging. Risk of over-staging was minimized to 7% in batch 3-4. N-staging remained unreliable with an overall accuracy of 61%. Pathologic review identified two tumor characteristics causing under-staging for T-stage in 5/7 cases: (1) very limited invasive part beyond the muscularis propria and (2) mucinous composition of the invading part. CONCLUSION: The high accuracy and specificity of T-staging reached in our study indicate that sufficient training and practice of experienced radiologists can ensure high validity for CT staging in colon cancer to safely use neoadjuvant therapy without significant risk of over-treatment, while N-staging remained unreliable.

Novel Approaches in Molecular Characterization of Classical Hodgkin Lymphoma.

Classical Hodgkin lymphoma (cHL) represents a B-cell lymphoproliferative disease characterized by clonal immunoglobulin gene rearrangements and recurrent genomic aberrations in the Hodgkin Reed-Sternberg cells in a reactive inflammatory background. Several methods are available for the molecular analysis of cHL on both tissue and cell-free DNA isolated from blood, which can provide detailed information regarding the clonal composition and genetic alterations that drive lymphoma pathogenesis. Clonality testing involving the detection of immunoglobulin and T cell receptor gene rearrangements, together with mutation analysis, represent valuable tools for cHL diagnostics, especially for patients with an atypical histological or clinical presentation reminiscent of a reactive lesion or another lymphoma subtype. In addition, clonality assessment may establish the clonal relationship of composite or subsequent lymphoma presentations within one patient. During the last few decades, more insight has been obtained on the molecular mechanisms that drive cHL development, including recurrently affected signaling pathways (e.g., NF-κB and JAK/STAT) and immune evasion. We provide an overview of the different approaches to characterize the molecular composition of cHL, and the implementation of these next-generation sequencing-based techniques in research and diagnostic settings.

Determining clinical course of diffuse large B-cell lymphoma using targeted transcriptome and machine learning algorithms.

Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology; however, these biological subgroups overlap clinically. Using machine learning, we developed an approach to stratify patients with DLBCL into four subgroups based on survival characteristics. This approach uses data from the targeted transcriptome to predict these survival subgroups. Using the expression levels of 180 genes, our model reliably predicted the four survival subgroups and was validated using independent groups of patients. Multivariate analysis showed that this patient stratification strategy encompasses various biological characteristics of DLBCL, and only TP53 mutations remained an independent prognostic biomarker. This novel approach for stratifying patients with DLBCL, based on the clinical outcome of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone therapy, can be used to identify patients who may not respond well to these types of therapy, but would otherwise benefit from alternative therapy and clinical trials.

Genetic Subtyping and Phenotypic Characterization of the Immune Microenvironment and MYC/BCL2 Double Expression Reveal Heterogeneity in Diffuse Large B-cell Lymphoma.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. RESULTS: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1-high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. CONCLUSIONS: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

Clonality assessment and detection of clonal diversity in classic Hodgkin lymphoma by next-generation sequencing of immunoglobulin gene rearrangements.

Clonality analysis in classic Hodgkin lymphoma (cHL) is of added value for correctly diagnosing patients with atypical presentation or histology reminiscent of T cell lymphoma, and for establishing the clonal relationship in patients with recurrent disease. However, such analysis has been hampered by the sparsity of malignant Hodgkin and Reed-Sternberg (HRS) cells in a background of reactive immune cells. Recently, the EuroClonality-NGS Working Group developed a novel next-generation sequencing (NGS)-based assay and bioinformatics platform (ARResT/Interrogate) to detect immunoglobulin (IG) gene rearrangements for clonality testing in B-cell lymphoproliferations. Here, we demonstrate the improved performance of IG-NGS compared to conventional BIOMED-2/EuroClonality analysis to detect clonal gene rearrangements in 16 well-characterized primary cHL cases within the IG heavy chain (IGH) and kappa light chain (IGK) loci. This was most obvious in formalin-fixed paraffin-embedded (FFPE) tissue specimens, where three times more clonal cases were detected with IG-NGS (9 cases) compared to BIOMED-2 (3 cases). In total, almost four times more clonal rearrangements were detected in FFPE with IG-NGS (N = 23) as compared to BIOMED-2/EuroClonality (N = 6) as judged on identical IGH and IGK targets. The same clonal rearrangements were also identified in paired fresh frozen cHL samples. To validate the neoplastic origin of the detected clonotypes, IG-NGS clonality analysis was performed on isolated HRS cells, demonstrating identical clonotypes as detected in cHL whole-tissue specimens. Interestingly, IG-NGS and HRS single-cell analysis after DEPArray™ digital sorting revealed rearrangement patterns and copy number variation profiles indicating clonal diversity and intratumoral heterogeneity in cHL. Our data demonstrate improved performance of NGS-based detection of IG gene rearrangements in cHL whole-tissue specimens, providing a sensitive molecular diagnostic assay for clonality assessment in Hodgkin lymphoma.

Tumour-stroma ratio outperforms tumour budding as biomarker in colon cancer: a cohort study.

The tumour-stroma ratio (TSR) and tumour budding (TB) are two high-risk factors with potential to be implemented in the next TNM classification. The aim of the current study was to evaluate the practical application of the two biomarkers based on reproducibility, independency and prognostic value. Patients diagnosed with stage II or III colon cancer who underwent surgery between 2005 and 2016 were included. Both TSR and TB were scored on haematoxylin and eosin-stained tissue sections. The TSR, based on the relative amount of stroma, was scored in increments of 10%. TB was scored following the consensus guidelines; a bud was defined as ≤ 4 tumour cells. For analysis, three categories were used. Cohen's kappa was used for reproducibility. The prognostic value was determined with survival analysis. In total, 246 patients were included. The TSR distribution was N = 137 (56%) stroma-low and N = 109 (44%) stroma-high. The TB distribution was TB-low N = 194 (79%), TB-intermediate N = 35 (14%) and TB-high N = 17 (7%). The reproducibility of the TSR was good (interobserver agreement kappa = 0.83 and intraobserver agreement kappa = 0.82), whereas the inter- and intraobserver agreement for scoring TB was moderate (kappa 0.47 and 0.45, respectively). The survival analysis showed an independent prognostic value for disease-free survival for TSR (HR 1.57; 95% CI 1.01-2.44; p = 0.048) and for TB-high (HR 2.01; 95% CI 1.02-3.96; p = 0.043). Based on current results, we suggest the TSR is a more reliable parameter in daily practice due to better reproducibility and independent prognostic value for disease-free survival.

Genomic complexity is associated with epigenetic regulator mutations and poor prognosis in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma with high mutation burdens but a low response rate to immune checkpoint inhibitors. In this study, we performed targeted next-generation sequencing and fluorescent multiplex immunohistochemistry, and investigated the clinical significance and immunological effect of mutation numbers in 424 DLBCL patients treated with standard immunochemotherapy. We found that KMT2D and TP53 nonsynonymous mutations (MUT) were significantly associated with increased nonsynonymous mutation numbers, and that high mutation numbers (MUThigh) were associated with significantly poorer clinical outcome in germinal center B-cell-like DLBCL with wild-type TP53. To understand the underlying mechanisms, we identified a gene-expression profiling signature and the association of MUThigh with decreased T cells in DLBCL patients with wild-type TP53. On the other hand, in overall cohort, MUThigh was associated with lower PD-1 expression in T cells and PD-L1 expression in macrophages, suggesting a positive role of MUThigh in immune responses. Analysis in a whole-exome sequencing dataset of 304 patients deposited by Chapuy et al. validated the correlation of MUT-KMT2D with genomic complexity and the significantly poorer survival associated with higher numbers of genomic single nucleotide variants in activated B-cell-like DLBCL with wild-type TP53. Together, these results suggest that KMT2D inactivation or epigenetic dysregulation has a role in driving DLBCL genomic instability, and that genomic complexity has adverse impact on clinical outcome in DLBCL patients with wild-type TP53 treated with standard immunochemotherapy. The oncoimmune data in this study have important implications for biomarker and therapeutic studies in DLBCL.

Daily practice in guideline adherence to adjuvant chemotherapy in stage III colon cancer and predictors of outcome.

INTRODUCTION: Although guidelines recommend adjuvant chemotherapy for stage III colon cancer patients, many patients do not receive adjuvant chemotherapy. The aim of this study was to identify reasons for guideline non-adherence and assess the effect on patient outcomes in a multicenter cohort of stage III colon cancer patients who received surgery plus adjuvant chemotherapy or surgery alone. METHODS: Patients who underwent surgery between 2007 and 2017 were included. Reasons for non-adherence were determined. Propensity score analyses with inverse probability weighting were performed to adjust for confounding factors. Cox proportional hazards regression and risk stratified analyses were performed to assess the association of guideline adherence and other potential predictors with recurrence free survival (RFS). RESULTS: Data of 575 patients were included of whom 61% received adjuvant chemotherapy. In 87 of 222 patients (39%) who did not receive adjuvant chemotherapy, no reason was documented. Only age was predictive for receiving chemotherapy. Patients who received adjuvant chemotherapy had longer RFS (HR 0.42, 95%CI 0.29-0.62, p < 0.001). High T- and N-stage were associated with poorer RFS HR 2.0 (95%CI 1.58-2.71, p < 0.001) and HR 2.19 (95%CI 1.60-2.99, p < 0.001) respectively. Risk groups were identified with distinct prognosis and treatment effect and a nomogram is presented to visualize individualized RFS differences. CONCLUSION: This study shows considerable variation in guideline adherence to adjuvant chemotherapy and poor documentation on reasons for non-adherence. Optimizing adherence and gaining insight in reasons for non-adherence is advocated as this can lead to significant RFS benefit, especially in patients with high T-and N-stage tumors.

e-Learning for Instruction and to Improve Reproducibility of Scoring Tumor-Stroma Ratio in Colon Carcinoma: Performance and Reproducibility Assessment in the UNITED Study.

BACKGROUND: The amount of stroma in the primary tumor is an important prognostic parameter. The tumor-stroma ratio (TSR) was previously validated by international research groups as a robust parameter with good interobserver agreement. OBJECTIVE: The Uniform Noting for International Application of the Tumor-Stroma Ratio as an Easy Diagnostic Tool (UNITED) study was developed to bring the TSR to clinical implementation. As part of the study, an e-Learning module was constructed to confirm the reproducibility of scoring the TSR after proper instruction. METHODS: The e-Learning module consists of an autoinstruction for TSR determination (instruction video or written protocol) and three sets of 40 cases (training, test, and repetition sets). Scoring the TSR is performed on hematoxylin and eosin-stained sections and takes only 1-2 minutes. Cases are considered stroma-low if the amount of stroma is ≤50%, whereas a stroma-high case is defined as >50% stroma. Inter- and intraobserver agreements were determined based on the Cohen κ score after each set to evaluate the reproducibility. RESULTS: Pathologists and pathology residents (N=63) with special interest in colorectal cancer participated in the e-Learning. Forty-nine participants started the e-Learning and 31 (63%) finished the whole cycle (3 sets). A significant improvement was observed from the training set to the test set; the median κ score improved from 0.72 to 0.77 (P=.002). CONCLUSIONS: e-Learning is an effective method to instruct pathologists and pathology residents for scoring the TSR. The reliability of scoring improved from the training to the test set and did not fall back with the repetition set, confirming the reproducibility of the TSR scoring method. TRIAL REGISTRATION: The Netherlands Trial Registry NTR7270; https://www.trialregister.nl/trial/7072. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13464.