Artificial intelligence, molecular subtyping, biomarkers, and precision oncology

A targeted cancer therapy is only useful if there is a way to accurately identify the tumors that are susceptible to that therapy. Thus rapid expansion in the number of available targeted cancer treatments has been accompanied by a robust effort to subdivide the traditional histological and anatomical tumor classifications into molecularly defined subtypes. This review highlights the history of the paired evolution of targeted therapies and biomarkers, reviews currently used methods for subtype identification, and discusses challenges to the implementation of precision oncology as well as possible solutions.

Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models

To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is-in contrast to melanoma-not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.

Synthetic Lethal Networks for Precision Oncology: Promises and Pitfalls

Synthetic lethal interactions, in which the simultaneous loss of function of two genes produces a lethal phenotype, are being explored as a means to therapeutically exploit cancer-specific vulnerabilities and expand the scope of precision oncology. Currently, three Food and Drug Administration-approved drugs work by targeting the synthetic lethal interaction between BRCA1/2 and PARP. This review examines additional efforts to discover networks of synthetic lethal interactions and discusses both challenges and opportunities regarding the translation of new synthetic lethal interactions into the clinic.

Piperine potentiates curcumin-mediated repression of mTORC1 signaling in human intestinal epithelial cells: implications for the inhibition of protein synthesis and TNFα signaling

Persistent activation of the mechanistic target of rapamycin complex 1 (mTORC1) is linked to sustained inflammation and progression of colorectal cancer. Widely available dietary phenolics, curcumin and piperine are purported to have antiinflammatory and anticarcinogenic activities through yet-to-be-delineated multitarget mechanisms. Piperine is also known to increase the bioavailability of dietary components, including curcumin. The objective of the study was to determine whether curcumin and piperine have individual and combined effects in the setting of gut inflammation by regulating mTORC1 in human intestinal epithelial cells. Results show that curcumin repressed (a) mTORC1 activity (measured as changes in the phosphorylation state of p70 ribosomal protein S6 kinase B1 and 40S ribosomal protein S6) in a dose-dependent manner (2.5-20 μM, P<.007) and (b) synthesis of nascent proteins. Piperine inhibited mTORC1 activity albeit at comparatively higher concentrations than curcumin. The combination of curcumin + piperine further repressed mTORC1 signaling (P<.02). Mechanistically, curcumin may repress mTORC1 by preventing TSC2 degradation, the conserved inhibitor of mTORC1. Results also show that a functional mTORC1 was required for the transcription of TNFα as Raptor knockdown abrogated TNFα gene expression. Curcumin, piperine and their combination inhibited TNFα gene expression at baseline but failed to do so under conditions of mTORC1 hyperactivation. TNF∝-induced cyclooxygenase-2 expression was repressed by curcumin or curcumin + piperine at baseline and high mTORC1 levels. We conclude that curcumin and piperine, either alone or in combination, have the potential to down-regulate mTORC1 signaling in the intestinal epithelium with implications for tumorigenesis and inflammation.

A phosphoarray platform is capable of personalizing kinase inhibitor therapy in head and neck cancers

Tyrosine kinase inhibitors are effective treatments for cancers. Knowing the specific kinase mutants that drive the underlying cancers predict therapeutic response to these inhibitors. Thus, the current protocol for personalized cancer therapy involves genotyping tumors in search of various driver mutations and subsequently individualizing the tyrosine kinase inhibitor to the patients whose tumors express the corresponding driver mutant. While this approach works when known driver mutations are found, its limitation is the dependence on driver mutations as predictors for response. To complement the genotype approach, we hypothesize that a phosphoarray platform is equally capable of personalizing kinase inhibitor therapy. We selected head and neck squamous cell carcinoma as the cancer model to test our hypothesis. Using the receptor tyrosine kinase phosphoarray, we identified the phosphorylation profiles of 49 different tyrosine kinase receptors in five different head and neck cancer cell lines. Based on these results, we tested the cell line response to the corresponding kinase inhibitor therapy. We found that this phosphoarray accurately informed the kinase inhibitor response profile of the cell lines. Next, we determined the phosphorylation profiles of 39 head and neck cancer patient derived xenografts. We found that absent phosphorylated EGFR signal predicted primary resistance to cetuximab treatment in the xenografts without phosphorylated ErbB2. Meanwhile, absent ErbB2 signaling in the xenografts with phosphorylated EGFR is associated with a higher likelihood of response to cetuximab. In summary, the phosphoarray technology has the potential to become a new diagnostic platform for personalized cancer therapy.

Impact of BRAF and RAS mutations on first-line efficacy of FOLFIRI plus cetuximab versus FOLFIRI plus bevacizumab: analysis of the FIRE-3 (AIO KRK-0306) study

BACKGROUND

RAS and BRAF mutations have been identified as negative prognostic factors in metastatic colorectal cancer. Efficacy of 5-fluorouracil, leucovorin, irinotecan (FOLFIRI) plus bevacizumab in patients with RAS-mutant tumours needs to be further evaluated. Whether to treat patients with BRAF-mutant tumours with either bevacizumab or anti-epidermal growth factor receptor (EGFR) antibodies remains unclear.

METHODS

Patients treated within the FIRE-3 trial were retrospectively tested for BRAF and RAS mutations using formalin fixated paraffin embedded (FFPE) tumour material applying pyrosequencing for KRAS and NRAS exon 2, 3 and 4 mutations as far as for BRAF mutations. Survival analysis was done using Kaplan-Meier estimation and differences were expressed using the log-rank test. Overall response rate (ORR) was compared using Fisher's exact test. Data from a central independent radiological response evaluation were used to calculate early tumour shrinkage (ETS) and depth of response (DpR).

RESULTS

Overall, 188 patients with RAS-mutant tumours and 48 with BRAF-mutant tumours were identified. In BRAF-mutant patients, ORR was numerically higher in the cetuximab versus the bevacizumab arm (52% versus 40%), while comparable results were achieved for progression-free survival (PFS; hazard ratio [HR] = 0.84, p = 0.56) and overall survival (OS; HR 0.79, p = 0.45). RAS mutation was associated with a trend towards lower ORR (37% versus 50.5%, p = 0.11) and shorter PFS (7.4 versus 9.7 months; HR 1.25; p = 0.14) in patients receiving FOLFIRI plus cetuximab versus bevacizumab, but OS was comparable (19.1 versus 20.1 months; HR 1.05; p = 0.73), respectively. ETS identified subgroups sensitive to cetuximab-based treatment in both BRAF- (9/17) and RAS-mutant (18/48) patients and was associated with significantly longer OS. DpR was comparable between both treatment arms in RAS- and BRAF-mutant patients, respectively.

CONCLUSIONS

In BRAF- and RAS-mutant patients, cetuximab- and bevacizumab-based treatment had comparable survival times. ETS represents an early parameter associated with the benefit from anti-EGFR, while this was not the case with vascular endothelial growth factor A blockade.

Single and Combination Drug Screening with Aqueous Biphasic Tumor Spheroids

Spheroids of cancer cells represent a physiologic model of solid tumors for cancer drug screening. Despite this known benefit, difficulties with generating large quantities of uniformly sized spheroids in standard plates, individually addressing spheroids with drug compounds, and quantitatively analyzing responses of cancer cells have hindered the use of spheroids in high-throughput screening applications. Recently, we addressed this challenge by using an aqueous two-phase system technology to generate a spheroid within an aqueous drop immersed in a second, immiscible aqueous phase. Integrating this approach with robotics resulted in convenient formation, maintenance, and drug treatment of spheroids. Here, we demonstrate the feasibility of high-throughput compound screening against colon cancer spheroids using 25 anticancer compounds. Using a strictly standardized mean difference and based on a preliminary testing with each compound, we select effective compounds for further dose-response testing. Finally, we use molecular inhibitors to target upregulated protein kinases and use them for drug combination studies against spheroids. We quantitatively analyze the combination treatment results using statistical metrics to identify synergy between pairs of inhibitors in compromising viability of colon cancer cells. This study demonstrates the utility of our spheroid culture technology for identification of effective drug compounds, dose-response analysis, and combination drug treatments.

Cancer subtypes classification using long non-coding RNA

Inter-tumor heterogeneity might explain divergent clinical evolution of cancers bearing similar pathological features. In the last decade, genomic has highly improved tumor subtypes classification through the identification of oncogenic or tumor suppressor drivers. In addition, epigenetics and long non-coding RNAs (lncRNAs) are emerging as new fields for investigation, which might also account for tumor heterogeneity. There is growing evidence that modifications of lncRNA expression profiles are involved in cancer progression through epigenetic regulation, activation of pro-oncogenic pathways and crosstalks with other RNA subtypes. Consequently, the study of lncRNA expression profile will be a key factor in the future for charting cancer subtype classifications as well as defining prognostic and progression biomarkers. Herein we discuss the interest of lncRNA as potent prognostic and predictive biomarkers, and provide a glimpse on the impact of emerging cancer subtypes classification based on lncRNAs.