Genomic and transcriptomic determinants of response to neoadjuvant therapy in rectal cancer.

The incidence of rectal cancer is increasing in patients younger than 50 years. Locally advanced rectal cancer is still treated with neoadjuvant radiation, chemotherapy and surgery, but recent evidence suggests that patients with a complete response can avoid surgery permanently. To define correlates of response to neoadjuvant therapy, we analyzed genomic and transcriptomic profiles of 738 untreated rectal cancers. APC mutations were less frequent in the lower than in the middle and upper rectum, which could explain the more aggressive behavior of distal tumors. No somatic alterations had significant associations with response to neoadjuvant therapy in a treatment-agnostic manner, but KRAS mutations were associated with faster relapse in patients treated with neoadjuvant chemoradiation followed by consolidative chemotherapy. Overexpression of IGF2 and L1CAM was associated with decreased response to neoadjuvant therapy. RNA-sequencing estimates of immune infiltration identified a subset of microsatellite-stable immune hot tumors with increased response and prolonged disease-free survival.

Privacy preserving validation for multiomic prediction models.

Reproducibility of results obtained using ribonucleic acid (RNA) data across labs remains a major hurdle in cancer research. Often, molecular predictors trained on one dataset cannot be applied to another due to differences in RNA library preparation and quantification, which inhibits the validation of predictors across labs. While current RNA correction algorithms reduce these differences, they require simultaneous access to patient-level data from all datasets, which necessitates the sharing of training data for predictors when sharing predictors. Here, we describe SpinAdapt, an unsupervised RNA correction algorithm that enables the transfer of molecular models without requiring access to patient-level data. It computes data corrections only via aggregate statistics of each dataset, thereby maintaining patient data privacy. Despite an inherent trade-off between privacy and performance, SpinAdapt outperforms current correction methods, like Seurat and ComBat, on publicly available cancer studies, including TCGA and ICGC. Furthermore, SpinAdapt can correct new samples, thereby enabling unbiased evaluation on validation cohorts. We expect this novel correction paradigm to enhance research reproducibility and to preserve patient privacy.

KRAS Mutants Upregulate Integrin ß4 to Promote Invasion and Metastasis in Colorectal Cancer.

KRAS mutation in colorectal cancer is associated with aggressive tumor behavior through increased invasiveness and higher rates of lung metastases, but the biological mechanisms behind these features are not fully understood. In this study, we show that KRAS-mutant colorectal cancer upregulates integrin α6ß4 through ERK/MEK signaling. Knocking-out integrin ß4 (ITGB4) specifically depleted the expression of integrin α6ß4 and this resulted in a reduction in the invasion and migration ability of the cancer cells. We also observed a reduction in the number and area of lung metastatic foci in mice that were injected with ITGB4 knockout KRAS-mutant colorectal cancer cells compared with the mice injected with ITGB4 wild-type KRAS-mutant colorectal cancer cells, while no difference was observed in liver metastases. Inhibiting integrin α6ß4 in KRAS-mutant colorectal cancer could be a potential therapeutic target to diminish the KRAS-invasive phenotype and associated pulmonary metastasis rate. IMPLICATIONS: Knocking-out ITGB4, which is overexpressed in KRAS-mutant colorectal cancer and promotes tumor aggressiveness, diminishes local invasiveness and rates of pulmonary metastasis.

KRAS mutant rectal cancer cells interact with surrounding fibroblasts to deplete the extracellular matrix.

Somatic mutations in the KRAS oncogene are associated with poor outcomes in locally advanced rectal cancer but the underlying biologic mechanisms are not fully understood. We profiled mRNA in 76 locally advanced rectal adenocarcinomas from patients that were enrolled in a prospective clinical trial and investigated differences in gene expression between KRAS mutant (KRAS-mt) and KRAS-wild-type (KRAS-wt) patients. We found that KRAS-mt tumors display lower expression of genes related to the tumor stroma and remodeling of the extracellular matrix. We validated our findings using samples from The Cancer Genome Atlas (TCGA) and also by performing immunohistochemistry (IHC) and immunofluorescence (IF) in orthogonal cohorts. Using in vitro and in vivo models, we show that oncogenic KRAS signaling within the epithelial cancer cells modulates the activity of the surrounding fibroblasts in the tumor microenvironment.

A rectal cancer organoid platform to study individual responses to chemoradiation.

Rectal cancer (RC) is a challenging disease to treat that requires chemotherapy, radiation and surgery to optimize outcomes for individual patients. No accurate model of RC exists to answer fundamental research questions relevant to patients. We established a biorepository of 65 patient-derived RC organoid cultures (tumoroids) from patients with primary, metastatic or recurrent disease. RC tumoroids retained molecular features of the tumors from which they were derived, and their ex vivo responses to clinically relevant chemotherapy and radiation treatment correlated with the clinical responses noted in individual patients' tumors. Upon engraftment into murine rectal mucosa, human RC tumoroids gave rise to invasive RC followed by metastasis to lung and liver. Importantly, engrafted tumors displayed the heterogenous sensitivity to chemotherapy observed clinically. Thus, the biology and drug sensitivity of RC clinical isolates can be efficiently interrogated using an organoid-based, ex vivo platform coupled with in vivo endoluminal propagation in animals.

Radiogenomics of rectal adenocarcinoma in the era of precision medicine: A pilot study of associations between qualitative and quantitative MRI imaging features and genetic mutations.

OBJECTIVE: To investigate associations between genetic mutations and qualitative as well as quantitative features on MRI in rectal adenocarcinoma at primary staging. METHODS: In this retrospective study, patients with rectal adenocarcinoma, genome sequencing, and pretreatment rectal MRI were included. Statistical analysis was performed to evaluate associations between qualitative features obtained from subjective evaluation of rectal MRI and gene mutations as well as between quantitative textural features and gene mutations. For the qualitative evaluation, Fisher's Exact test was used to analyze categorical associations and Wilcoxon Rank Sum test was used for continuous clinical variables. For the quantitative evaluation, we performed manual segmentation of T2-weighted images for radiomics-based quantitative image analysis. Thirty-four texture features consisting of first order intensity histogram-based features (n = 4), second order Haralick textures (n = 5), and Gabor-edge based Haralick textures were computed at two different orientations. Consensus clustering was performed with 34 computed texture features using the K-means algorithm with Euclidean distance between the texture features. The clusters resulting from the algorithm were then used to enumerate the prevalence of gene mutations in those clusters. RESULTS: In 65 patients, 45 genes were mutated in more than 3/65 patients (5%) and were included in the statistical analysis. Regarding qualitative imaging features, on univariate analysis, tumor location was significantly associated with APC (p = 0.032) and RASA1 mutation (p = 0.032); CRM status was significantly associated with ATM mutation (p = 0.021); and lymph node metastasis was significantly associated with BRCA2 (p = 0.046) mutation. However, these associations were not significant after adjusting for multiple comparisons. Regarding quantitative imaging features, Cluster C1 had tumors with higher mean Gabor edge intensity compared with cluster C2 (θ = 0°, p = 0.018; θ = 45°, p = 0.047; θ = 90°, p = 0.037; cluster C3 (θ = 0°, p = 0.18; θ = 45°, p = 0.1; θ = 90°, p = 0.052), and cluster C4 (θ = 0°, p = 0.016; θ = 45°, p = 0.033; θ = 90°, p = 0.014) suggesting that the cluster C1 had tumors with more distinct edges or heterogeneous appearance compared with other clusters. CONCLUSIONS: Although this preliminary study showed promising associations between quantitative features and genetic mutations, it did not show any correlation between qualitative features and genetic mutations. Further studies with larger sample size are warranted to validate our preliminary data.

MET activation confers resistance to cetuximab, and prevents HER2 and HER3 upregulation in head and neck cancer.

An understanding of the mechanisms underlying acquired resistance to cetuximab is urgently needed to improve cetuximab efficacy in patients with head and neck squamous cell carcinoma (HNSCC). Here, we present a clinical observation that MET pathway activation constitutes the mechanism of acquired resistance to cetuximab in a patient with HNSCC. Specifically, RNA sequencing and mass spectrometry analysis of cetuximab-sensitive (CetuxSen ) and cetuximab-resistant (CetuxRes ) tumors indicated MET amplification and overexpression in the CetuxRes tumor compared to the CetuxSen lesion. Stimulation of MET in HNSCC cell lines was sufficient to reactivate the MAPK pathway and to confer resistance to cetuximab in vitro and in vivo. In addition to the direct role of MET in reactivation of the MAPK pathway, MET stimulation abrogates the well-known cetuximab-induced compensatory feedback loop of HER2/HER3 expression. Mechanistically, we showed that the overexpression of HER2 and HER3 following cetuximab treatment is mediated by the ETS homologous transcription factor (EHF), and is suppressed by MET/MAPK pathway activation. Collectively, our findings indicate that evaluation of MET and HER2/HER3 in response to cetuximab in HNSCC patients can provide the rationale of successive line of treatment.

Genomic Landscape of Pancreatic Adenocarcinoma in Younger versus Older Patients: Does Age Matter?

PURPOSE: State-of-the-art genomic analyses of pancreatic adenocarcinoma (PDAC) have yielded insight into signaling pathways underlying carcinogenesis. PDAC is characterized by substantial genomic heterogeneity. We aimed to determine whether early-onset PDAC (EOPC; ≤55 years) displays a distinctive molecular landscape from average-age onset PDAC (AOPC; ≥70 years). EXPERIMENTAL DESIGN: Three distinct datasets for PDAC were analyzed. In the first, patients undergoing treatment at Memorial Sloan Kettering (MSK) were consented for MSK-IMPACT next-generation sequencing. The second cohort analyzed was The Cancer Genome Atlas (TCGA) dataset for differences in somatic mutations, gene expression, and protein expression. The third dataset was an Australian cohort of PDAC. Clinical data were correlated with genomic analyses. RESULTS: A total of 293 samples were analyzed, yielding 90 patients aged ≤55 years and 203 patients aged ≥70 years. Among the genes known to be associated with carcinogenesis, SMAD4 displayed higher mutation rates in younger patients. Comprehensive transcriptomic analysis of cellular pathways indicated that the TGFß pathway has increased activation, and the expression levels of phospho-GSK3 were higher in EOPC. Survival outcomes revealed no differences between age groups. CONCLUSIONS: These exploratory analyses suggest that there may be somatic gene alterations within the population of patients with early-onset PDAC that involve unique cellular pathways compared with average-onset PDAC. Former studies imply these cellular pathways may play a role in smoking-related PDAC carcinogenesis. Larger genomic datasets are warranted for future evaluation to extend these observations.

Consolidation mFOLFOX6 Chemotherapy After Chemoradiotherapy Improves Survival in Patients With Locally Advanced Rectal Cancer: Final Results of a Multicenter Phase II Trial.

BACKGROUND: Adding modified FOLFOX6 (folinic acid, fluorouracil, and oxaliplatin) after chemoradiotherapy and lengthening the chemoradiotherapy-to-surgery interval is associated with an increase in the proportion of rectal cancer patients with a pathological complete response. OBJECTIVE: The purpose of this study was to analyze disease-free and overall survival. DESIGN: This was a nonrandomized phase II trial. SETTINGS: The study was conducted at multiple institutions. PATIENTS: Four sequential study groups with stage II or III rectal cancer were included. INTERVENTION: All of the patients received 50 Gy of radiation with concurrent continuous infusion of fluorouracil for 5 weeks. Patients in each group received 0, 2, 4, or 6 cycles of modified FOLFOX6 after chemoradiation and before total mesorectal excision. Patients were recommended to receive adjuvant chemotherapy after surgery to complete a total of 8 cycles of modified FOLFOX6. MAIN OUTCOME MEASURES: The trial was powered to detect differences in pathological complete response, which was reported previously. Disease-free and overall survival are the main outcomes for the current study. RESULTS: Of 259 patients, 211 had a complete follow-up. Median follow-up was 59 months (range, 9-125 mo). The mean number of total chemotherapy cycles differed among the 4 groups (p = 0.002), because one third of patients in the group assigned to no preoperative FOLFOX did not receive any adjuvant chemotherapy. Disease-free survival was significantly associated with study group, ypTNM stage, and pathological complete response (p = 0.004, <0.001, and 0.001). A secondary analysis including only patients who received ≥1 cycle of FOLFOX still showed differences in survival between study groups (p = 0.03). LIMITATIONS: The trial was not randomized and was not powered to show differences in survival. Survival data were not available for 19% of the patients. CONCLUSIONS: Adding modified FOLFOX6 after chemoradiotherapy and before total mesorectal excision increases compliance with systemic chemotherapy and disease-free survival in patients with locally advanced rectal cancer. Neoadjuvant consolidation chemotherapy may have benefits beyond increasing pathological complete response rates. See Video Abstract at http://links.lww.com/DCR/A739.

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data.

Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts-for example, distance-dependent random polymer ligation and GC content and mappability bias-and model zero inflation and overdispersion. Applied to high-resolution Hi-C data in a lymphoblastoid cell line, HiC-DC detects significant interactions at the sub-topologically associating domain level, identifying potential structural and regulatory interactions supported by CTCF binding sites, DNase accessibility, and/or active histone marks. CTCF-associated interactions are most strongly enriched in the middle genomic distance range (∼700 kb-1.5 Mb), while interactions involving actively marked DNase accessible elements are enriched both at short (<500 kb) and longer (>1.5 Mb) genomic distances. There is a striking enrichment of longer-range interactions connecting replication-dependent histone genes on chromosome 6, potentially representing the chromatin architecture at the histone locus body.

Prediction of potent shRNAs with a sequential classification algorithm.

We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

KRAS and Combined KRAS/TP53 Mutations in Locally Advanced Rectal Cancer are Independently Associated with Decreased Response to Neoadjuvant Therapy.

BACKGROUND: The response of rectal cancers to neoadjuvant chemoradiation (CRT) is variable, but tools to predict response remain lacking. We evaluated whether KRAS and TP53 mutations are associated with pathologic complete response (pCR) and lymph node metastasis after adjusting for neoadjuvant regimen. METHODS: Retrospective analysis of 229 pretreatment biopsies from patients with stage II/III rectal cancer was performed. All patients received CRT. Patients received 0-8 cycles of FOLFOX either before or after CRT, but prior to surgical excision. A subset was analyzed to assess concordance between mutation calls by Sanger Sequencing and a next-generation assay. RESULTS: A total of 96 tumors (42 %) had KRAS mutation, 150 had TP53 mutation (66 %), and 59 (26 %) had both. Following neoadjuvant therapy, 59 patients (26 %) achieved pCR. Of 133 KRAS wild-type tumors, 45 (34 %) had pCR, compared with 14 of 96 (15 %) KRAS mutant tumors (p = .001). KRAS mutation remained independently associated with a lower pCR rate on multivariable analysis after adjusting for clinical stage, CRT-to-surgery interval and cycles of FOLFOX (OR 0.34; 95 % CI 0.17-0.66, p < .01). Of 29 patients with KRAS G12V or G13D, only 2 (7 %) achieved pCR. Tumors with both KRAS and TP53 mutation were associated with lymph node metastasis. The concordance between platforms was high for KRAS (40 of 43, 93 %). CONCLUSIONS: KRAS mutation is independently associated with a lower pCR rate in locally advanced rectal cancer after adjusting for variations in neoadjuvant regimen. Genomic data can potentially be used to select patients for "watch and wait" strategies.

Integrated genomic profiling identifies microRNA-92a regulation of IQGAP2 in locally advanced rectal cancer.

Locally advanced rectal cancer (LARC) is treated with chemoradiation prior to surgical excision, leaving residual tumors altered or completely absent. Integrating layers of genomic profiling might identify regulatory pathways relevant to rectal tumorigenesis and inform therapeutic decisions and further research. We utilized formalin-fixed, paraffin-embedded pre-treatment LARC biopsies (n=138) and compared copy number, mRNA, and miRNA expression with matched normal rectal mucosa. An integrative model was used to predict regulatory interactions to explain gene expression changes. These predictions were evaluated in vitro using multiple colorectal cancer cell lines. The Cancer Genome Atlas (TCGA) was also used as an external cohort to validate our genomic profiling and predictions. We found differentially expressed mRNAs and miRNAs that characterize LARC. Our integrative model predicted the upregulation of miR-92a, miR-182, and miR-221 expression to be associated with downregulation of their target genes after adjusting for the effect of copy number alterations. Cell line studies using miR-92a mimics and inhibitors demonstrate that miR-92a expression regulates IQGAP2 expression. We show that endogenous miR-92a expression is inversely associated with endogenous KLF4 expression in multiple cell lines, and that this relationship is also present in rectal cancers of TCGA. Our integrative model predicted regulators of gene expression change in LARC using pre-treatment FFPE tissues. Our methodology implicated multiple regulatory interactions, some of which are corroborated by independent lines of study, while others indicate new opportunities for investigation.

Affinity regression predicts the recognition code of nucleic acid-binding proteins.

Predicting the affinity profiles of nucleic acid-binding proteins directly from the protein sequence is a challenging problem. We present a statistical approach for learning the recognition code of a family of transcription factors or RNA-binding proteins (RBPs) from high-throughput binding data. Our method, called affinity regression, trains on protein binding microarray (PBM) or RNAcompete data to learn an interaction model between proteins and nucleic acids using only protein domain and probe sequences as inputs. When trained on mouse homeodomain PBM profiles, our model correctly identifies residues that confer DNA-binding specificity and accurately predicts binding motifs for an independent set of divergent homeodomains. Similarly, when trained on RNAcompete profiles for diverse RBPs, our model correctly predicts the binding affinities of held-out proteins and identifies key RNA-binding residues, despite the high level of sequence divergence across RBPs. We expect that the method will be broadly applicable to modeling and predicting paired macromolecular interactions in settings where high-throughput affinity data are available.

AXL mediates resistance to PI3Kα inhibition by activating the EGFR/PKC/mTOR axis in head and neck and esophageal squamous cell carcinomas.

Phosphoinositide-3-kinase (PI3K)-α inhibitors have shown clinical activity in squamous cell carcinomas (SCCs) of head and neck (H&N) bearing PIK3CA mutations or amplification. Studying models of therapeutic resistance, we have observed that SCC cells that become refractory to PI3Kα inhibition maintain PI3K-independent activation of the mammalian target of rapamycin (mTOR). This persistent mTOR activation is mediated by the tyrosine kinase receptor AXL. AXL is overexpressed in resistant tumors from both laboratory models and patients treated with the PI3Kα inhibitor BYL719. AXL dimerizes with and phosphorylates epidermal growth factor receptor (EGFR), resulting in activation of phospholipase Cγ (PLCγ)-protein kinase C (PKC), which, in turn, activates mTOR. Combined treatment with PI3Kα and either EGFR, AXL, or PKC inhibitors reverts this resistance.

Linking signaling pathways to transcriptional programs in breast cancer.

Cancer cells acquire genetic and epigenetic alterations that often lead to dysregulation of oncogenic signal transduction pathways, which in turn alters downstream transcriptional programs. Numerous methods attempt to deduce aberrant signaling pathways in tumors from mRNA data alone, but these pathway analysis approaches remain qualitative and imprecise. In this study, we present a statistical method to link upstream signaling to downstream transcriptional response by exploiting reverse phase protein array (RPPA) and mRNA expression data in The Cancer Genome Atlas (TCGA) breast cancer project. Formally, we use an algorithm called affinity regression to learn an interaction matrix between upstream signal transduction proteins and downstream transcription factors (TFs) that explains target gene expression. The trained model can then predict the TF activity, given a tumor sample's protein expression profile, or infer the signaling protein activity, given a tumor sample's gene expression profile. Breast cancers are comprised of molecularly distinct subtypes that respond differently to pathway-targeted therapies. We trained our model on the TCGA breast cancer data set and identified subtype-specific and common TF regulators of gene expression. We then used the trained tumor model to predict signaling protein activity in a panel of breast cancer cell lines for which gene expression and drug response data was available. Correlations between inferred protein activities and drug responses in breast cancer cell lines grouped several drugs that are clinically used in combination. Finally, inferred protein activity predicted the clinical outcome within the METABRIC Luminal A cohort, identifying high- and low-risk patient groups within this heterogeneous subtype.

Impact of RNA-guided technologies for target identification and deconvolution.

For well over a decade, RNA interference (RNAi) has provided a powerful tool for investigators to query specific gene targets in an easily modulated loss-of-function setting, both in vitro and in vivo. Hundreds of publications have demonstrated the utility of RNAi in arrayed and pooled-based formats, in a wide variety of cell-based systems, including clonal, stem, transformed, and primary cells. Over the years, there have been significant improvements in the design of target-specific small-interfering RNA (siRNA) and short-hairpin RNA (shRNA), expression vectors, methods for mitigating off-target effects, and accurately interpreting screening results. Recent developments in RNAi technology include the Sensor assay, high-efficiency miR-E shRNAs, improved shRNA virus production with Pasha (DRGC8) knockdown, and assessment of RNAi off-target effects by using the C9-11 method. An exciting addition to the arsenal of RNA-mediated gene modulation is the clustered regularly interspaced short palindromic repeats/Cas9 (CRISPR/Cas) system for genomic editing, allowing for gene functional knockout rather than knockdown.