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Purpose:The DNA damage immune response (DDIR) assay was developed in breast cancer based on biology associated with deficiencies in homologous recombination and Fanconi anemia pathways. A positive DDIR call identifies patients likely to respond to platinum-based chemotherapies in breast and esophageal cancers. In colorectal cancer, there is currently no biomarker to predict response to oxaliplatin. We tested the ability of the DDIR assay to predict response to oxaliplatin-based chemotherapy in colorectal cancer and characterized the biology in DDIR-positive colorectal cancer.Experimental Design:Samples and clinical data were assessed according to DDIR status from patients who received either 5-fluorouracil (5-FU) or 5FUFA (bolus and infusion 5-FU with folinic acid) plus oxaliplatin (FOLFOX) within the FOCUS trial (n = 361, stage IV), or neoadjuvant FOLFOX in the FOxTROT trial (n = 97, stage II/III). Whole transcriptome, mutation, and IHC data of these samples were used to interrogate the biology of DDIR in colorectal cancer.Results:Contrary to our hypothesis, DDIR-negative patients displayed a trend toward improved outcome for oxaliplatin-based chemotherapy compared with DDIR-positive patients. DDIR positivity was associated with microsatellite instability (MSI) and colorectal molecular subtype 1. Refinement of the DDIR signature, based on overlapping IFN-related chemokine signaling associated with DDIR positivity across colorectal cancer and breast cancer cohorts, further confirmed that the DDIR assay did not have predictive value for oxaliplatin-based chemotherapy in colorectal cancer.Conclusions:DDIR positivity does not predict improved response following oxaliplatin treatment in colorectal cancer. However, data presented here suggest the potential of the DDIR assay in identifying immune-rich tumors that may benefit from immune checkpoint blockade, beyond current use of MSI status.

Supplementary Results

Figures S1-S9, Tables S1, S2

supplementary methods

Supplementary Methods and Table 1. Supplementary Table 1: siRNA target genes

Ataxia telangiectasia mutated (ATM) is an important signaling molecule in the DNA damage response (DDR). ATM loss of function can produce a synthetic lethal phenotype in combination with tumor-associated mutations in FA/BRCA pathway components. In this study, we took an siRNA screening strategy to identify other tumor suppressors that, when inhibited, similarly sensitized cells to ATM inhibition. In this manner, we determined that PTEN and ATM were synthetically lethal when jointly inhibited. PTEN-deficient cells exhibited elevated levels of reactive oxygen species, increased endogenous DNA damage, and constitutive ATM activation. ATM inhibition caused catastrophic DNA damage, mitotic cell cycle arrest, and apoptosis specifically in PTEN-deficient cells in comparison with wild-type cells. Antioxidants abrogated the increase in DNA damage and ATM activation in PTEN-deficient cells, suggesting a requirement for oxidative DNA damage in the mechanism of cell death. Lastly, the ATM inhibitor KU-60019 was specifically toxic to PTEN mutant cancer cells in tumor xenografts and reversible by reintroduction of wild-type PTEN. Together, our results offer a mechanistic rationale for clinical evaluation of ATM inhibitors in PTEN-deficient tumors. Cancer Res; 75(11); 2159–65. ©2015 AACR.

Supplementary Figures 1-4. Figure 1: ATM is a potential drug target for PTEN-deficient cells Figure 2: The synthetic lethality with PTEN loss and ATM inhibition is independent of AKT function Figure 3: The synthetic lethality with PTEN loss and ATM inhibition is independent of RAD51 function Supplementary Figure 4: In vivo efficacy of ATM inhibition with PTEN loss

Objective Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. Design Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. Results Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. Conclusion This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.

This case describes how a leader of a financial institution used systems thinking as a foresight tool to help survive global economic crisis during the Great Recession of 2008. Due to the leader’s systems thinking perspective, several behavioral themes emerged. Organizational policies were then developed to help institutionalize these behaviors. The outcome for the organization was successful response to an oncoming global economic catastrophe. Strategic management strategies, supporting futures thinking, ultimately guided and stabilized the organization throughout this economic crisis, effectively leading to future growth.

The PTEN (phosphatase and tensin homologue deleted on chromosome 10) tumour suppressor is a phosphatidylinositol 3,4,5-trisphosphate [PtdIns(3,4,5)P3] 3-phosphatase that plays a critical role in regulating many cellular processes by antagonizing the phosphoinositide 3-kinase signalling pathway. We have identified and characterized two human homologues of PTEN, which differ with respect to their subcellular localization and lipid phosphatase activities. The previously cloned, but uncharacterized, TPTE (transmembrane phosphatase with tensin homology) is localized to the plasma membrane, but lacks detectable phosphoinositide 3-phosphatase activity. TPIP (TPTE and PTEN homologous inositol lipid phosphatase) is a novel phosphatase that occurs in several differentially spliced forms of which two, TPIPα and TPIPβ, appear to be functionally distinct. TPIPα displays similar phosphoinositide 3-phosphatase activity compared with PTEN against PtdIns(3,4,5)P3, PtdIns(3,5)P2, PtdIns(3,4)P2 and PtdIns(3)P, has N-terminal transmembrane domains and appears to be localized on the endoplasmic reticulum. This is unusual as most signalling-lipid-metabolizing enzymes are not integral membrane proteins. TPIPβ, however, lacks detectable phosphatase activity and is cytosolic. TPIP has a wider tissue distribution than the testis-specific TPTE, with specific splice variants being expressed in testis, brain and stomach. TPTE and TPIP do not appear to be functional orthologues of the Golgi-localized and more distantly related murine PTEN2. We suggest that TPIPα plays a role in regulating phosphoinositide signalling on the endoplasmic reticulum, and might also represent a tumour suppressor and functional homologue of PTEN in some tissues.