Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression–based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, evident metabolic dysregulation; and CMS4 (Mesenchymal, 23%), prominent transforming growth factor β activation, stromal invasion, and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intra-tumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC – with clear biological interpretability – and the basis for future clinical stratification and subtype–based targeted interventions.

Current measures of health and disease are often insensitive, episodic, and subjective. Further, these measures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease. Benefitting from large enrollment and repeated measurements on many individuals, these data may help establish baseline variability of real-world activity measurement collected via mobile phones, and ultimately may lead to quantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collection modules are available through an open source license for use in studies of other conditions. We hope that releasing data contributed by engaged research participants will seed a new community of analysts working collaboratively on understanding mobile health data to advance human health.

Background & Aims Categorization of colon cancers into distinct subtypes using a combination of pathway-based biomarkers could provide insight into stage-independent variability in outcomes. Methods We used a PCR-based assay to detect mutations in BRAF (V600E) and in KRAS in 2720 stage III cancer samples, collected prospectively from patients participating in an adjuvant chemotherapy trial (NCCTG N0147). Tumors deficient or proficient in DNA mismatch repair (MMR) were identified based on detection of MLH1, MSH2, and MSH6 proteins and methylation of the MLH1 promoter. Findings were validated using tumor samples from a separate set of patients with stage III cancer (n=783). Association with 5-year disease-free survival was evaluated using Cox proportional hazards models. Results Tumors were categorized into 5 subtypes based on MMR status and detection of BRAFV600E or mutations in KRAS, which were mutually exclusive. Three subtypes were MMR proficient: those with BRAFV600E (6.9% of samples), mutations in KRAS (35%), or tumors lacking either BRAFV600E or mutations in KRAS (49%). Two subtypes were MMR deficient: the sporadic type (6.8%) with BRAFV600E or hypermethylation of MLH1, and the familial type (2.6%), which lacked BRAFV600E or hypermethylation of MLH1. A higher percentage of MMR-proficient tumors with BRAFV600E were proximal (76%), high grade (44%), N2 stage (59%), and detected in women (59%), compared to MMR-proficient tumors without BRAFV600E or mutations in KRAS (33%, 19%, 41%, and 42%, respectively; all P<.0001). A significantly lower proportion of patients with MMR-proficient tumors with BRAFV600E (hazard ratio, 1.43; 95% confidence interval, 1.11–1.85, Padjusted=.0065) or mutant KRAS (hazard ratio, 1.48; 95% confidence interval, 1.27–1.74, Padjusted<.0001) survived disease free for 5 years compared to patients whose MMR-proficient tumors lacked mutations in either gene. Disease-free survival of patients with MMR-deficient sporadic or familial subtypes was similar to that of patients with MMR-proficient tumors without BRAFV600E or mutations in KRAS. The observed differences in survival of patients with different tumor subtypes was validated in an independent cohort. Conclusions We identified subtypes of stage III colon cancer, based on detection of mutations in BRAF (V600E) or KRAS, and MMR status that show differences in clinical and pathologic features and disease-free survival. Patients with MMR-proficient tumors and BRAFV600E or mutations in KRAS had statistically shorter survival times than patients whose tumors lacked these mutations. The tumor subtype found in nearly half of the study cohort (MMR-proficient without BRAFV600E or KRAS mutations) had similar outcomes to those of patients with MMR-deficient cancers.

BackgroundTNM staging alone does not accurately predict outcome in colon cancer (CC) patients who may be eligible for adjuvant chemotherapy. It is unknown to what extent the molecular markers microsatellite instability (MSI) and mutations in BRAF or KRAS improve prognostic estimation in multivariable models that include detailed clinicopathological annotation.Patients and methodsAfter imputation of missing at random data, a subset of patients accrued in phase 3 trials with adjuvant chemotherapy (n = 3016)—N0147 (NCT00079274) and PETACC3 (NCT00026273)—was aggregated to construct multivariable Cox models for 5-year overall survival that were subsequently validated internally in the remaining clinical trial samples (n = 1499), and also externally in different population cohorts of chemotherapy-treated (n = 949) or -untreated (n = 1080) CC patients, and an additional series without treatment annotation (n = 782).ResultsTNM staging, MSI and BRAFV600E mutation status remained independent prognostic factors in multivariable models across clinical trials cohorts and observational studies. Concordance indices increased from 0.61–0.68 in the TNM alone model to 0.63–0.71 in models with added molecular markers, 0.65–0.73 with clinicopathological features and 0.66–0.74 with all covariates. In validation cohorts with complete annotation, the integrated time-dependent AUC rose from 0.64 for the TNM alone model to 0.67 for models that included clinicopathological features, with or without molecular markers. In patient cohorts that received adjuvant chemotherapy, the relative proportion of variance explained (R2) by TNM, clinicopathological features and molecular markers was on an average 65%, 25% and 10%, respectively.ConclusionsIncorporation of MSI, BRAFV600E and KRAS mutation status to overall survival models with TNM staging improves the ability to precisely prognosticate in stage II and III CC patients, but only modestly increases prediction accuracy in multivariable models that include clinicopathological features, particularly in chemotherapy-treated patients.