STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer

Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes.

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems

Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.

Bile acid distributions, sex-specificity, and prognosis in colorectal cancer

BACKGROUND

Bile acids are known to be genotoxic and contribute to colorectal cancer (CRC). However, the link between CRC tumor bile acids to tumor location, patient sex, microbiome, immune-regulatory cells, and prognosis is not clear.

METHODS

We conducted bile acid analysis using targeted liquid chromatography-mass spectrometry (LC-MS) on tumor tissues from CRC patients (n = 228) with survival analysis. We performed quantitative immunofluorescence (QIF) on tumors to examine immune cells.

RESULTS

Twelve of the bile acids were significantly higher in right-sided colon tumors compared to left-sided colon tumors. Furthermore, in male patients, right-sided colon tumors had elevated secondary bile acids (deoxycholic acid, lithocholic acid, ursodeoxycholic acid) compared to left-sided colon tumors, but this difference between tumors by location was not observed in females. A high ratio of glycoursodeoxycholic to ursodeoxycholic was associated with 5-year overall survival (HR = 3.76, 95% CI = 1.17 to 12.1, P = 0.026), and a high ratio of glycochenodeoxycholic acid to chenodeoxycholic acid was associated with 5-year recurrence-free survival (HR = 3.61, 95% CI = 1.10 to 11.84, P = 0.034). We also show correlation between these bile acids and FoxP3 + T regulatory cells.

CONCLUSIONS

This study revealed that the distribution of bile acid abundances in colon cancer patients is tumor location-, age- and sex-specific, and are linked to patient prognosis. This study provides new implications for targeting bile acid metabolism, microbiome, and immune responses for colon cancer patients by taking into account primary tumor location and sex.

Activation of the NRF2 antioxidant program sensitizes tumors to G6PD inhibition

The KEAP1/NRF2 pathway promotes metabolic rewiring to support redox homeostasis. Activation of NRF2 occurs in many cancers, often due to KEAP1 mutations, and is associated with more aggressive disease and treatment resistance. To identify metabolic dependencies in cancers with NRF2 activation, we performed a metabolism-focused CRISPR screen. Glucose-6-phosphate dehydrogenase (G6PD), which was recently shown to be dispensable in Ras-driven tumors, was a top dependency. G6PD catalyzes the committed step of the oxidative pentose phosphate pathway that produces NADPH and nucleotide precursors, but neither antioxidants nor nucleosides rescued. Instead, G6PD loss triggered tricarboxylic acid (TCA) intermediate depletion because of up-regulation of the alternative NADPH-producing enzymes malic enzyme and isocitrate dehydrogenase. In vivo, G6PD impairment markedly suppressed KEAP1 mutant tumor growth, and this suppression was further augmented by TCA depletion by glutaminase inhibition. Thus, G6PD inhibition–induced TCA depletion is a therapeutic vulnerability of NRF2-activated cancer.

Discovery and Features of an Alkylating Signature in Colorectal Cancer

Several risk factors have been established for colorectal cancer, yet their direct mutagenic effects in patients' tumors remain to be elucidated. Here, we leveraged whole-exome sequencing data from 900 colorectal cancer cases that had occurred in three U.S.-wide prospective studies with extensive dietary and lifestyle information. We found an alkylating signature that was previously undescribed in colorectal cancer and then showed the existence of a similar mutational process in normal colonic crypts. This alkylating signature is associated with high intakes of processed and unprocessed red meat prior to diagnosis. In addition, this signature was more abundant in the distal colorectum, predicted to target cancer driver mutations KRAS p.G12D, KRAS p.G13D, and PIK3CA p.E545K, and associated with poor survival. Together, these results link for the first time a colorectal mutational signature to a component of diet and further implicate the role of red meat in colorectal cancer initiation and progression. SIGNIFICANCE: Colorectal cancer has several lifestyle risk factors, but the underlying mutations for most have not been observed directly in tumors. Analysis of 900 colorectal cancers with whole-exome sequencing and epidemiologic annotations revealed an alkylating mutational signature that was associated with red meat consumption and distal tumor location, as well as predicted to target KRAS p.G12D/p.G13D.This article is highlighted in the In This Issue feature, p. 2355.