Multiplex analysis of intratumoural immune infiltrate and prognosis in patients with stage II-III colorectal cancer from the SCOT and QUASAR 2 trials: a retrospective analysis.

BACKGROUND: Tumour-infiltrating CD8+ cytotoxic T cells confer favourable prognosis in colorectal cancer. The added prognostic value of other infiltrating immune cells is unclear and so we sought to investigate their prognostic value in two large clinical trial cohorts. METHODS: We used multiplex immunofluorescent staining of tissue microarrays to assess the densities of CD8+, CD20+, FoxP3+, and CD68+ cells in the intraepithelial and intrastromal compartments from tumour samples of patients with stage II-III colorectal cancer from the SCOT trial (ISRCTN59757862), which examined 3 months versus 6 months of adjuvant oxaliplatin-based chemotherapy, and from the QUASAR 2 trial (ISRCTN45133151), which compared adjuvant capecitabine with or without bevacizumab. Both trials included patients aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0-1. Immune marker predictors were analysed by multiple regression, and the prognostic and predictive values of markers for colorectal cancer recurrence-free interval by Cox regression were assessed using the SCOT cohort for discovery and QUASAR 2 cohort for validation. FINDINGS: After exclusion of cases without tissue microarrays and with technical failures, and following quality control, we included 2340 cases from the SCOT trial and 1069 from the QUASAR 2 trial in our analysis. Univariable analysis of associations with recurrence-free interval in cases from the SCOT trial showed a strong prognostic value of intraepithelial CD8 (CD8IE) as a continuous variable (hazard ratio [HR] for 75th vs 25th percentile [75vs25] 0·73 [95% CI 0·68-0·79], p=2·5 × 10-16), and of intrastromal FoxP3 (FoxP3IS; 0·71 [0·64-0·78], p=1·5 × 10-13) but not as strongly in the epithelium (FoxP3IE; 0·89 [0·84-0·96], p=1·5 × 10-4). Associations of other markers with recurrence-free interval were moderate. CD8IE and FoxP3IS retained independent prognostic value in bivariable and multivariable analysis, and, compared with either marker alone, a composite marker including both markers (CD8IE-FoxP3IS) was superior when assessed as a continuous variable (adjusted [a]HR75 vs 25 0·70 [95% CI 0·63-0·78], p=5·1 × 10-11) and when categorised into low, intermediate, and high density groups using previously published cutpoints (aHR for intermediate vs high 1·68 [95% CI 1·29-2·20], p=1·3 × 10-4; low vs high 2·58 [1·91-3·49], p=7·9 × 10-10), with performance similar to the gold-standard Immunoscore. The prognostic value of CD8IE-FoxP3IS was confirmed in cases from the QUASAR 2 trial, both as a continuous variable (aHR75 vs 25 0·84 [95% CI 0·73-0·96], p=0·012) and as a categorical variable for low versus high density (aHR 1·80 [95% CI 1·17-2·75], p=0·0071) but not for intermediate versus high (1·30 [0·89-1·88], p=0·17). INTERPRETATION: Combined evaluation of CD8IE and FoxP3IS could help to refine risk stratification in colorectal cancer. Investigation of FoxP3IS cells as an immunotherapy target in colorectal cancer might be merited. FUNDING: Medical Research Council, National Institute for Health Research, Cancer Research UK, Swedish Cancer Society, Roche, and Promedica Foundation.

VertXNet: an ensemble method for vertebral body segmentation and identification from cervical and lumbar spinal X-rays.

Accurate annotation of vertebral bodies is crucial for automating the analysis of spinal X-ray images. However, manual annotation of these structures is a laborious and costly process due to their complex nature, including small sizes and varying shapes. To address this challenge and expedite the annotation process, we propose an ensemble pipeline called VertXNet. This pipeline currently combines two segmentation mechanisms, semantic segmentation using U-Net, and instance segmentation using Mask R-CNN, to automatically segment and label vertebral bodies in lateral cervical and lumbar spinal X-ray images. VertXNet enhances its effectiveness by adopting a rule-based strategy (termed the ensemble rule) for effectively combining segmentation outcomes from U-Net and Mask R-CNN. It determines vertebral body labels by recognizing specific reference vertebral instances, such as cervical vertebra 2 ('C2') in cervical spine X-rays and sacral vertebra 1 ('S1') in lumbar spine X-rays. Those references are commonly relatively easy to identify at the edge of the spine. To assess the performance of our proposed pipeline, we conducted evaluations on three spinal X-ray datasets, including two in-house datasets and one publicly available dataset. The ground truth annotations were provided by radiologists for comparison. Our experimental results have shown that the proposed pipeline outperformed two state-of-the-art (SOTA) segmentation models on our test dataset with a mean Dice of 0.90, vs. a mean Dice of 0.73 for Mask R-CNN and 0.72 for U-Net. We also demonstrated that VertXNet is a modular pipeline that enables using other SOTA model, like nnU-Net to further improve its performance. Furthermore, to evaluate the generalization ability of VertXNet on spinal X-rays, we directly tested the pre-trained pipeline on two additional datasets. A consistently strong performance was observed, with mean Dice coefficients of 0.89 and 0.88, respectively. In summary, VertXNet demonstrated significantly improved performance in vertebral body segmentation and labeling for spinal X-ray imaging. Its robustness and generalization were presented through the evaluation of both in-house clinical trial data and publicly available datasets.

Accounting for intensity variation in image analysis of large-scale multiplexed clinical trial datasets.

Multiplex immunofluorescence (mIF) imaging can provide comprehensive quantitative and spatial information for multiple immune markers for tumour immunoprofiling. However, application at scale to clinical trial samples sourced from multiple institutions is challenging due to pre-analytical heterogeneity. This study reports an analytical approach to the largest multi-parameter immunoprofiling study of clinical trial samples to date. We analysed 12,592 tissue microarray (TMA) spots from 3,545 colorectal cancers sourced from more than 240 institutions in two clinical trials (QUASAR 2 and SCOT) stained for CD4, CD8, CD20, CD68, FoxP3, pan-cytokeratin, and DAPI by mIF. TMA slides were multi-spectrally imaged and analysed by cell-based and pixel-based marker analysis. We developed an adaptive thresholding method to account for inter- and intra-slide intensity variation in TMA analysis. Applying this method effectively ameliorated inter- and intra-slide intensity variation improving the image analysis results compared with methods using a single global threshold. Correlation of CD8 data derived by our mIF analysis approach with single-plex chromogenic immunohistochemistry CD8 data derived from subsequent sections indicates the validity of our method (Spearman's rank correlation coefficients ρ between 0.63 and 0.66, p ≪ 0.01) as compared with the current gold standard analysis approach. Evaluation of correlation between cell-based and pixel-based analysis results confirms equivalency (ρ > 0.8, p ≪ 0.01, except for CD20 in the epithelial region) of both analytical approaches. These data suggest that our adaptive thresholding approach can enable analysis of mIF-stained clinical trial TMA datasets by digital pathology at scale for precision immunoprofiling.

Estimation of the worldwide seroprevalence of cytomegalovirus: A systematic review and meta-analysis.

Cytomegalovirus (CMV) infection does not usually produce symptoms when it causes primary infection, reinfection, or reactivation because these three types of infection are all controlled by the normal immune system. However, CMV becomes an important pathogen in individuals whose immune system is immature or compromised, such as the unborn child. Several vaccines against CMV are currently in clinical trials that aim to induce immunity in seronegative individuals and/or to boost the immunity of those with prior natural infection (seropositives). To facilitate estimation of the burden of disease and the need for vaccines that induce de novo immune responses or that boost pre-existing immunity to CMV, we conducted a systematic survey of the published literature to describe the global seroprevalence of CMV IgG antibodies. We estimated a global CMV seroprevalence of 83% (95%UI: 78-88) in the general population, 86% (95%UI: 83-89) in women of childbearing age, and 86% (95%UI: 82-89) in donors of blood or organs. For each of these three groups, the highest seroprevalence was seen in the World Health Organisation (WHO) Eastern Mediterranean region 90% (95%UI: 85-94) and the lowest in WHO European region 66% (95%UI: 56-74). These estimates of the worldwide CMV distribution will help develop national and regional burden of disease models and inform future vaccine development efforts.

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.