Long-term Survival Update and Extended RAS Mutational Analysis of the CAIRO2 Trial: Addition of Cetuximab to CAPOX/Bevacizumab in Metastatic Colorectal Cancer.

BACKGROUND: Here we present updated survival of the CAIRO2 trial and assessed whether the addition of anti-EGFR to anti-VEGF therapy could still be an effective treatment option for patients with extended RAS/BRAF wildtype and left-sided metastatic colorectal cancer (mCRC). MATERIALS AND METHODS: Retrospective updated survival and extended RAS and BRAF V600E mutational analysis were performed in the CAIRO2 trial, a multicenter, randomized phase III trial on the effect of adding cetuximab to a combination of capecitabine, oxaliplatin (CAPOX), and bevacizumab in mCRC. RESULTS: Updated survival analysis confirmed that the addition of cetuximab did not provide a benefit on either progression free (PFS) or overall survival (OS) in the intention-to-treat population. With the extended mutational analyses 31 KRAS, 31 NRAS and 12 BRAF V600E additional mutations were found. No benefit of the addition of cetuximab was observed within the extended wildtype group, even when selecting only left-sided tumors (PFS HR 0.96, p = 0.7775). However, compared to the original trial an increase of 6.5 months was seen for patients with both extended wildtype and left-sided tumors (median OS 28.6 months). CONCLUSION: Adding cetuximab to CAPOX and bevacizumab does not provide clinical benefit in patients with mCRC, even in the extended wildtype group with left-sided tumors. However, in the extended wildtype group we did observe clinically relevant higher survival compared to the initial trial report, indicating that it is important to analyze a broader panel of RAS and BRAF variants using more recent sequencing techniques when assessing survival benefit after anti-EGFR therapy.

Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity.

Intra-tumor heterogeneity (ITH) is a pan-cancer predictor of survival, with high ITH being correlated to a dismal prognosis. The level of ITH is, hence, a clinically relevant characteristic of a malignancy. ITH of karyotypes is driven by chromosomal instability (CIN). However, not all new karyotypes generated by CIN are viable or competitive, which limits the amount of ITH. Here, we review the cellular processes and ecological properties that determine karyotype ITH. We propose a framework to understand karyotype ITH, in which cells with new karyotypes emerge through CIN, are selected by cell intrinsic and cell extrinsic selective pressures, and propagate through a cancer in competition with other malignant cells. We further discuss how CIN modulates the cell phenotype and immune microenvironment, and the implications this has for the subsequent selection of karyotypes. Together, we aim to provide a comprehensive overview of the biological processes that shape the level of karyotype heterogeneity.

Molecular characterization of colorectal cancer related peritoneal metastatic disease.

A significant proportion of colorectal cancer (CRC) patients develop peritoneal metastases (PM) in the course of their disease. PMs are associated with a poor quality of life, significant morbidity and dismal disease outcome. To improve care for this patient group, a better understanding of the molecular characteristics of CRC-PM is required. Here we present a comprehensive molecular characterization of a cohort of 52 patients. This reveals that CRC-PM represent a distinct CRC molecular subtype, CMS4, but can be further divided in three separate categories, each presenting with unique features. We uncover that the CMS4-associated structural protein Moesin plays a key role in peritoneal dissemination. Finally, we define specific evolutionary features of CRC-PM which indicate that polyclonal metastatic seeding underlies these lesions. Together our results suggest that CRC-PM should be perceived as a distinct disease entity.

Copy number heterogeneity identifies ER+ breast cancer patients that do not benefit from adjuvant endocrine therapy.

BACKGROUND: Endocrine therapy forms the backbone of adjuvant treatment for oestrogen-receptor-positive (ER+) breast cancer. However, it remains unclear whether adjuvant treatment improves survival rates in low-risk patients. Low intra-tumour heterogeneity (ITH) has been shown to confer low risk for recurrent disease. Here, it is studied if chromosomal copy-number ITH (CNH) can identify low-risk ER+, lymph-node-negative breast cancer patients who do not benefit from adjuvant endocrine therapy. METHODS: Lymph-node-negative ER+ patients from the observational METABRIC dataset were retrospectively analysed (n = 708). CNH was determined from a single bulk copy-number measurement for each patient. Survival rates were compared between patients that did or did not receive adjuvant endocrine therapy for CNH-low, middle and high groups with Cox proportional-hazards models, using propensity-score weights to correct for confounders. RESULTS: Adjuvant endocrine therapy improved the relapse-free survival (RFS) for CNH-high patients treatment (HR = 0.55), but not for CNH-low patients treatment (HR = 0.88). For CNH-low patients adjuvant endocrine therapy was associated with impaired OS (HR = 1.62). CONCLUSIONS: This retrospective study of lymph-node-negative, ER+ breast cancer finds that patients identified as low risk using CNH do not benefit from adjuvant endocrine therapy.

Copy-number intratumor heterogeneity as high-risk feature of stage II colon cancer†.

Overall, the prognosis of patients suffering from stage II colon cancer is relatively favorable. However, a proportion of patients develop a recurrence following surgery. Clinical and histopathological properties that identify high-risk patients are of limited value and better biomarkers are urgently required. In a recent issue of The Journal of Pathology, Lahoz et al proposed that copy-number-based biomarkers could be employed for patient stratification. The authors studied copy-number alterations (CNAs) at the genomic scale by measuring the total CNA load (the aberrant genome fraction), and at a smaller scale by identifying common arm- or cytoband-level alterations. Both the overall CNA load and specific chromosomal regions were associated with an increased risk of recurrence. Most interestingly, it was demonstrated that copy-number intratumor heterogeneity, as defined by subclonal CNAs, is associated with poor disease outcome. This study demonstrates that structural genomic aberrations are promising biomarkers for patient stratification in early colon cancer. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Predicting survival of cancer patients by chromosomal copy number heterogeneity.

We recently introduced a method to derive intra-tumor heterogeneity (ITH) from a single copy number measurement. This method stratifies patients for survival and could potentially help to identify low and high-risk patients with clinical relevance.

Marker-free lineage tracing reveals an environment-instructed clonogenic hierarchy in pancreatic cancer.

Effective treatments for pancreatic ductal adenocarcinoma (PDAC) are lacking, and targeted agents have demonstrated limited efficacy. It has been speculated that a rare population of cancer stem cells (CSCs) drives growth, therapy resistance, and rapid metastatic progression in PDAC. These CSCs demonstrate high clonogenicity in vitro and tumorigenic potential in vivo. However, their relevance in established PDAC tissue has not been determined. Here, we use marker-independent stochastic clonal labeling, combined with quantitative modeling of tumor expansion, to uncover PDAC tissue growth dynamics. We find that in contrast to the CSC model, all PDAC cells display clonogenic potential in situ. Furthermore, the proximity to activated cancer-associated fibroblasts determines tumor cell clonogenicity. This means that the microenvironment is dominant in defining the clonogenic activity of PDAC cells. Indeed, manipulating the stroma by Hedgehog pathway inhibition alters the tumor growth mode, revealing that tumor-stroma crosstalk shapes tumor growth dynamics and clonal architecture.

Continuous clonal labeling reveals uniform progenitor potential in the adult exocrine pancreas.

The tissue dynamics that govern maintenance and regeneration of the pancreas remain largely unknown. In particular, the presence and nature of a cellular hierarchy remains a topic of debate. Previous lineage tracing strategies in the pancreas relied on specific marker genes for clonal labeling, which left other populations untested and failed to account for potential widespread phenotypical plasticity. Here we employed a tracing system that depends on replication-induced clonal marks. We found that, in homeostasis, steady acinar replacement events characterize tissue dynamics, to which all acinar cells have an equal ability to contribute. Similarly, regeneration following pancreatitis was best characterized by an acinar self-replication model because no evidence of a cellular hierarchy was detected. In particular, rapid regeneration in the pancreas was found to be driven by an accelerated rate of acinar fission-like events. These results provide a comprehensive and quantitative model of cell dynamics in the exocrine pancreas.

Chromosomal copy number heterogeneity predicts survival rates across cancers.

Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

Predictors of 30-Day Mortality Among Dutch Patients Undergoing Colorectal Cancer Surgery, 2011-2016.

Importance: Quality improvement programs for colorectal cancer surgery have been introduced with benchmarking based on quality indicators, such as mortality. Detailed (pre)operative characteristics may offer relevant information for proper case-mix correction. Objective: To investigate the added value of machine learning to predict quality indicators for colorectal cancer surgery and identify previously unrecognized predictors of 30-day mortality based on a large, nationwide colorectal cancer registry that collected extensive data on comorbidities. Design, Setting, and Participants: All patients who underwent resection for primary colorectal cancer registered in the Dutch ColoRectal Audit between January 1, 2011, and December 31, 2016, were included. Multiple machine learning models (multivariable logistic regression, elastic net regression, support vector machine, random forest, and gradient boosting) were made to predict quality indicators. Model performance was compared with conventionally used scores. Risk factors were identified by logistic regression analyses and Shapley additive explanations (ie, SHAP values). Statistical analysis was performed between March 1 and September 30, 2020. Main Outcomes and Measures: The primary outcome of this cohort study was 30-day mortality. Prediction models were trained on a training set by performing 5-fold cross-validation, and outcomes were measured by the area under the receiver operating characteristic curve on the test set. Machine learning was further used to identify risk factors, measured by odds ratios and SHAP values. Results: This cohort study included 62 501 records, most patients were male (35 116 [56.2%]), were aged 61 to 80 years (41 560 [66.5%]), and had an American Society of Anesthesiology score of II (35 679 [57.1%]). A 30-day mortality rate of 2.7% (n = 1693) was found. The area under the curve of the best machine learning model for 30-day mortality (0.82; 95% CI, 0.79-0.85) was significantly higher than the American Society of Anesthesiology score (0.74; 95% CI, 0.71-0.77; P < .001), Charlson Comorbidity Index (0.66; 95% CI, 0.63-0.70; P < .001), and preoperative score to predict postoperative mortality (0.73; 95% CI, 0.70-0.77; P < .001). Hypertension, myocardial infarction, chronic obstructive pulmonary disease, and asthma were comorbidities with a high risk for increased mortality. Machine learning identified specific risk factors for a complicated course, intensive care unit admission, prolonged hospital stay, and readmission. Laparoscopic surgery was associated with a decreased risk for all adverse outcomes. Conclusions and Relevance: This study found that machine learning methods outperformed conventional scores to predict 30-day mortality after colorectal cancer surgery, identified specific patient groups at risk for adverse outcomes, and provided directions to optimize benchmarking in clinical audits.

Stem cell functionality is microenvironmentally defined during tumour expansion and therapy response in colon cancer.

Solid malignancies have been speculated to depend on cancer stem cells (CSCs) for expansion and relapse after therapy. Here we report on quantitative analyses of lineage tracing data from primary colon cancer xenograft tissue to assess CSC functionality in a human solid malignancy. The temporally obtained clone size distribution data support a model in which stem cell function in established cancers is not intrinsically, but is entirely spatiotemporally orchestrated. Functional stem cells that drive tumour expansion predominantly reside at the tumour edge, close to cancer-associated fibroblasts. Hence, stem cell properties change in time depending on the cell location. Furthermore, although chemotherapy enriches for cells with a CSC phenotype, in this context functional stem cell properties are also fully defined by the microenvironment. To conclude, we identified osteopontin as a key cancer-associated fibroblast-produced factor that drives in situ clonogenicity in colon cancer.