Publications

Objectives: We set out to identify and characterize prophages within genomes of published Fusobacterium strains, and to develop qPCR-based methods to characterize intra- and extra-cellular induction of prophage replication in a variety of environmental contexts. Methods: Various in silico tools were used to predict prophage presence across 105 Fusobacterium spp. Genomes. Using the example of the model pathogen, Fusobacterium nucleatum subsp. animalis strain 7-1, qPCR was used with DNase I treatment to determine induction of its 3 predicted prophages ɸFunu1, ɸFunu2, and ɸFunu3, across several conditions. Results: 116 predicted prophage sequences were found and analyzed. An emerging association between the phylogenetic history of a Fusobacterium prophage and that of its host was detected, as was the presence of genes encoding putative host fitness factors (e.g. ADP-ribosyltransferases) in distinct subclusters of prophage genomes. For strain 7-1, a pattern of expression for ɸFunu1, ɸFunu2, and ɸFunu3 was established indicating that ɸFunu1 and ɸFunu2 are capable of spontaneous induction. I Salt and mitomycin C exposure were able to promote induction of ɸFunu2. A range of other biologically relevant stressors, including exposure to pH, mucin and human cytokines showed no or minimal induction of these same prophages. ɸFunu3 induction was not detected under tested conditions. Conclusion: The heterogeneity of Fusobacterium strains is matched by their prophages. While the role of Fusobacterium prophages in host pathogenicity remains unclear, this work provides the first overview of clustered prophage distribution among this enigmatic genus and describes an effective assay for quantifying mixed samples of prophages that cannot be detected by plaque assay.

INTRODUCTION: 

Early-onset colorectal cancer diagnosed before the age of 50 years has been increasing. Likely reflecting the pathogenic role of the intestinal microbiome, which gradually changes across the entire colorectal length, the prevalence of certain tumor molecular characteristics gradually changes along colorectal subsites. Understanding how colorectal tumor molecular features differ by age and tumor location is important in personalized patient management.

METHODS: 

Using 14,004 cases with colorectal cancer including 3,089 early-onset cases, we examined microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF mutations in carcinomas of the cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum and compared early-onset cases with later-onset cases.

RESULTS: 

The proportions of MSI-high, CIMP-high, and BRAF-mutated early-onset tumors were lowest in the rectum (8.8%, 3.4%, and 3.5%, respectively) and highest in the ascending colon (46% MSI-high; 15% CIMP-high) or transverse colon (8.6% BRAF-mutated) (all P_trend <0.001 across the rectum to ascending colon). Compared with later-onset tumors, early-onset tumors showed a higher prevalence of MSI-high status and a lower prevalence of CIMP-high status and BRAF mutations in most subsites. KRAS mutation prevalence was higher in the cecum compared with that in the other subsites in both early-onset and later-onset tumors (P < 0.001). Notably, later-onset MSI-high tumors showed a continuous decrease in KRAS mutation prevalence from the rectum (36%) to ascending colon (9%; P_trend <0.001), followed by an increase in the cecum (14%), while early-onset MSI-high cancers showed no such trend.

DISCUSSION: 

Our findings support biogeographical and pathogenic heterogeneity of colorectal carcinomas in different colorectal subsites and age groups.

Background

The pathogenic effect of colorectal tumor molecular features may be influenced by several factors, including those related to microbiota, inflammation, metabolism, and epigenetics, which may change along colorectal segments. We hypothesized that the prognostic association of colon cancer location might differ by tumor molecular characteristics.

Methods

Utilizing a consortium dataset of 13,101 colorectal cancer cases, including 2994 early-onset cases, we conducted survival analyses of detailed tumor location stratified by statuses of microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF oncogenic mutation.

Results

There was a statistically significant trend for better colon cancer-specific survival in relation to tumor location from the cecum to sigmoid colon (P_trend = 0.002), excluding the rectum. The prognostic association of colon location differed by MSI status (P_interaction = 0.001). Non-MSI-high tumors exhibited the cecum-to-sigmoid trend for better colon cancer-specific survival [P_trend < 0.001; multivariable hazard ratio (HR) for the sigmoid colon (vs. cecum), 0.80; 95% confidence interval (CI) 0.70–0.92], whereas MSI-high tumors demonstrated a suggestive cecum-to-sigmoid trend for worse survival (P_trend = 0.020; the corresponding HR, 2.13; 95% CI 1.15–3.92). The prognostic association of colon tumor location also differed by CIMP status (P_interaction = 0.003) but not significantly by age, stage, or other features. Furthermore, MSI-high status was a favorable prognostic indicator in all stages.

Conclusions

Both detailed colonic location and tumor molecular features need to be accounted for colon cancer prognostication to advance precision medicine. Our study indicates the important role of large-scale studies to robustly examine detailed colonic subsites in molecular oncology research.

Tumour heterogeneity is thought to be a major barrier to successful cancer treatment due to the presence of drug resistant clonal lineages. However, identifying the characteristics of such lineages that underpin resistance to therapy has remained challenging. Here, we utilise clonal transcriptomics with WILD-seq; Wholistic Interrogation of Lineage Dynamics by sequencing, in mouse models of triple-negative breast cancer (TNBC) to understand response and resistance to therapy, including BET bromodomain inhibition and taxane-based chemotherapy. These analyses revealed oxidative stress protection by NRF2 as a major mechanism of taxane resistance and led to the discovery that our tumour models are collaterally sensitive to asparagine deprivation therapy using the clinical stage drug L-asparaginase after frontline treatment with docetaxel. In summary, clonal transcriptomics with WILD-seq identifies mechanisms of resistance to chemotherapy that are also operative in patients and pin points asparagine bioavailability as a druggable vulnerability of taxane-resistant lineages.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability^1,2,3,4 patterned by distinct mutational processes^5,6, tumour heterogeneity^7,8,9 and intraperitoneal spread^7,8,10. Immunotherapies have had limited efficacy in HGSOC^11,12,13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8⁺ T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.