Advanced Centre for Treatment, Research and Education in Cancer

Abstract Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature 1 . Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses 3–15 , enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated—but distinct—DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.

Abstract Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale 1–3 . Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter 4 ; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation 5,6 ; analyses timings and patterns of tumour evolution 7 ; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity 8,9 ; and evaluates a range of more-specialized features of cancer genomes 8,10–18 .

Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been the subject of intense research over the past decades. In this paper, we introduce the "Automatic Cardiac Diagnosis Challenge" dataset (ACDC), the largest publicly available and fully annotated dataset for the purpose of cardiac MRI (CMR) assessment. The dataset contains data from 150 multi-equipments CMRI recordings with reference measurements and classification from two medical experts. The overarching objective of this paper is to measure how far state-of-the-art deep learning methods can go at assessing CMRI, i.e., segmenting the myocardium and the two ventricles as well as classifying pathologies. In the wake of the 2017 MICCAI-ACDC challenge, we report results from deep learning methods provided by nine research groups for the segmentation task and four groups for the classification task. Results show that the best methods faithfully reproduce the expert analysis, leading to a mean value of 0.97 correlation score for the automatic extraction of clinical indices and an accuracy of 0.96 for automatic diagnosis. These results clearly open the door to highly accurate and fully automatic analysis of cardiac CMRI. We also identify scenarios for which deep learning methods are still failing. Both the dataset and detailed results are publicly available online, while the platform will remain open for new submissions.

In anatomic pathology, immunohistochemistry (IHC) serves as a diagnostic and prognostic method for identification of disease markers in tissue samples that directly influences classification and grading the disease, influencing patient management. However, till today over most of the world, pathological analysis of tissue samples remained a time-consuming and subjective procedure, wherein the intensity of antibody staining is manually judged and thus scoring decision is directly influenced by visual bias. This instigated us to design a simple method of automated digital IHC image analysis algorithm for an unbiased, quantitative assessment of antibody staining intensity in tissue sections. As a first step, we adopted the spectral deconvolution method of DAB/hematoxylin color spectra by using optimized optical density vectors of the color deconvolution plugin for proper separation of the DAB color spectra. Then the DAB stained image is displayed in a new window wherein it undergoes pixel-by-pixel analysis, and displays the full profile along with its scoring decision. Based on the mathematical formula conceptualized, the algorithm is thoroughly tested by analyzing scores assigned to thousands (n = 1703) of DAB stained IHC images including sample images taken from human protein atlas web resource. The IHC Profiler plugin developed is compatible with the open resource digital image analysis software, ImageJ, which creates a pixel-by-pixel analysis profile of a digital IHC image and further assigns a score in a four tier system. A comparison study between manual pathological analysis and IHC Profiler resolved in a match of 88.6% (P<0.0001, CI = 95%). This new tool developed for clinical histopathological sample analysis can be adopted globally for scoring most protein targets where the marker protein expression is of cytoplasmic and/or nuclear type. We foresee that this method will minimize the problem of inter-observer variations across labs and further help in worldwide patient stratification potentially benefitting various multinational clinical trial initiatives.

Abstract Cancer develops through a process of somatic evolution 1,2 . Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes 3 . Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) 4 , we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.

Abstract A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes 1–7 . Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types 8 . Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions—as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2–7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and—in liver cancer—frequently activate the telomerase gene TERT . A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act.

BACKGROUND: Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. METHODOLOGY: In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. CONCLUSIONS: The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

Abstract The discovery of drivers of cancer has traditionally focused on protein-coding genes 1–4 . Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers 6,7 , raise doubts about others and identify novel candidates, including point mutations in the 5′ region of TP53 , in the 3′ untranslated regions of NFKBIZ and TOB1 , focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Abstract Transcript alterations often result from somatic changes in cancer genomes 1 . Various forms of RNA alterations have been described in cancer, including overexpression 2 , altered splicing 3 and gene fusions 4 ; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) 5 . Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis , of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed ‘bridged’ fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

PURPOSE Standard first-line therapy for EGFR-mutant advanced non–small-cell lung cancer (NSCLC) is an epidermal growth factor receptor (EGFR)–directed oral tyrosine kinase inhibitor. Adding pemetrexed and carboplatin chemotherapy to an oral tyrosine kinase inhibitor may improve outcomes. PATIENTS AND METHODS This was a phase III randomized trial in patients with advanced NSCLC harboring an EGFR-sensitizing mutation and a performance status of 0 to 2 who were planned to receive first-line palliative therapy. Random assignment was 1:1 to gefitinib 250 mg orally per day (Gef) or gefitinib 250 mg orally per day plus pemetrexed 500 mg/m 2 and carboplatin area under curve 5 intravenously every 3 weeks for four cycles, followed by maintenance pemetrexed (gefitinib plus chemotherapy [Gef+C]). The primary end point was progression-free survival (PFS); secondary end points included overall survival (OS), response rate, and toxicity. RESULTS Between 2016 and 2018, 350 patients were randomly assigned to Gef (n = 176) and Gef+C (n = 174). Twenty-one percent of patients had a performance status of 2, and 18% of patients had brain metastases. Median follow-up time was 17 months (range, 7 to 30 months). Radiologic response rates were 75% and 63% in the Gef+C and Gef arms, respectively ( P = .01). Estimated median PFS was significantly longer with Gef+C than Gef (16 months [95% CI, 13.5 to 18.5 months] v 8 months [95% CI, 7.0 to 9.0 months], respectively; hazard ratio for disease progression or death, 0.51 [95% CI, 0.39 to 0.66]; P &lt; .001). Estimated median OS was significantly longer with Gef+C than Gef (not reached v 17 months [95% CI, 13.5 to 20.5 months]; hazard ratio for death, 0.45 [95% CI, 0.31 to 0.65]; P &lt; .001). Clinically relevant grade 3 or greater toxicities occurred in 51% and 25% of patients in the Gef+C and Gef arms, respectively ( P &lt; .001). CONCLUSION Adding pemetrexed and carboplatin chemotherapy to gefitinib significantly prolonged PFS and OS but increased toxicity in patients with NSCLC.

Signal transducer and activator of transcription 3 (STAT3) is a latent cytoplasmic transcription factor, originally discovered as a transducer of signal from cell surface receptors to the nucleus. It is activated by tyrosine phosphorylation at position 705 leading to its dimerization, nuclear translocation, DNA binding, and activation of gene transcription. Under normal physiological conditions, STAT3 activation is tightly regulated. However, compelling evidence suggests that STAT3 is constitutively activated in many cancers and plays a pivotal role in tumor growth and metastasis. It regulates cellular proliferation, invasion, migration, and angiogenesis that are critical for cancer metastasis. In this paper, we first describe the mechanism of STAT3 regulation followed by how STAT3 is involved in cancer metastasis, then we summarize the various small molecule inhibitors that inhibit STAT3 signaling.

We report biodegradable plasmon resonant liposome gold nanoparticles (LiposAu NPs) capable of killing cancer cells through photothermal therapy. The pharmacokinetic study of LiposAu NPs performed in a small animal model indicates in situ degradation in hepatocytes and further getting cleared through the hepato-biliary and renal route. Further, the therapeutic potential of LiposAu NPs tested in mouse tumor xenograft model using NIR laser (750 nm) illumination resulted in complete ablation of the tumor mass, thus prolonging disease-free survival.

BACKGROUND: Squamous cell lung carcinomas account for approximately 25% of new lung carcinoma cases and 40,000 deaths per year in the United States. Although there are multiple genomically targeted therapies for lung adenocarcinoma, none has yet been reported in squamous cell lung carcinoma. METHODOLOGY/PRINCIPAL FINDINGS: Using SNP array analysis, we found that a region of chromosome segment 8p11-12 containing three genes-WHSC1L1, LETM2, and FGFR1-is amplified in 3% of lung adenocarcinomas and 21% of squamous cell lung carcinomas. Furthermore, we demonstrated that a non-small cell lung carcinoma cell line harboring focal amplification of FGFR1 is dependent on FGFR1 activity for cell growth, as treatment of this cell line either with FGFR1-specific shRNAs or with FGFR small molecule enzymatic inhibitors leads to cell growth inhibition. CONCLUSIONS/SIGNIFICANCE: These studies show that FGFR1 amplification is common in squamous cell lung cancer, and that FGFR1 may represent a promising therapeutic target in non-small cell lung cancer.

BACKGROUND AND PURPOSE: The Meta-Analysis of Chemotherapy in squamous cell Head and Neck Cancer (MACH-NC) demonstrated that concomitant chemotherapy (CT) improved overall survival (OS) in patients without distant metastasis. We report the updated results. MATERIALS AND METHODS: Published or unpublished randomized trials including patients with non-metastatic carcinoma randomized between 1965 and 2016 and comparing curative loco-regional treatment (LRT) to LRT + CT or adding another timing of CT to LRT + CT (main question), or comparing induction CT + radiotherapy to radiotherapy + concomitant (or alternating) CT (secondary question) were eligible. Individual patient data were collected and combined using a fixed-effect model. OS was the main endpoint. RESULTS: For the main question, 101 trials (18951 patients, median follow-up of 6.5 years) were analyzed. For both questions, there were 16 new (2767 patients) and 11 updated trials. Around 90% of the patients had stage III or IV disease. Interaction between treatment effect on OS and the timing of CT was significant (p < 0.0001), the benefit being limited to concomitant CT (HR: 0.83, 95%CI [0.79; 0.86]; 5(10)-year absolute benefit of 6.5% (3.6%)). Efficacy decreased as patients age increased (p_trend = 0.03). OS was not increased by the addition of induction (HR = 0.96 [0.90; 1.01]) or adjuvant CT (1.02 [0.92; 1.13]). Efficacy of induction CT decreased with poorer performance status (p_trend = 0.03). For the secondary question, eight trials (1214 patients) confirmed the superiority of concomitant CT on OS (HR = 0.84 [0.74; 0.95], p = 0.005). CONCLUSION: The update of MACH-NC confirms the benefit and superiority of the addition of concomitant CT for non-metastatic head and neck cancer.

Gingivo-buccal oral squamous cell carcinoma (OSCC-GB), an anatomical and clinical subtype of head and neck squamous cell carcinoma (HNSCC), is prevalent in regions where tobacco-chewing is common. Exome sequencing (n=50) and recurrence testing (n=60) reveals that some significantly and frequently altered genes are specific to OSCC-GB (USP9X, MLL4, ARID2, UNC13C and TRPM3), while some others are shared with HNSCC (for example, TP53, FAT1, CASP8, HRAS and NOTCH1). We also find new genes with recurrent amplifications (for example, DROSHA, YAP1) or homozygous deletions (for example, DDX3X) in OSCC-GB. We find a high proportion of C>G transversions among tobacco users with high numbers of mutations. Many pathways that are enriched for genomic alterations are specific to OSCC-GB. Our work reveals molecular subtypes with distinctive mutational profiles such as patients predominantly harbouring mutations in CASP8 with or without mutations in FAT1. Mean duration of disease-free survival is significantly elevated in some molecular subgroups. These findings open new avenues for biological characterization and exploration of therapies. Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the leading cancer among males in India. Here, the authors carry out exome sequencing and recurrence testing in patients with OSCC-GB and highlight genes and biological pathways associated with the disease.

PURPOSE We report the clinical outcomes of a randomized trial comparing prophylactic whole-pelvic nodal radiotherapy to prostate-only radiotherapy (PORT) in high-risk prostate cancer. METHODS This phase III, single center, randomized controlled trial enrolled eligible patients undergoing radical radiotherapy for node-negative prostate adenocarcinoma, with estimated nodal risk ≥ 20%. Randomization was 1:1 to PORT (68 Gy/25# to prostate) or whole-pelvic radiotherapy (WPRT, 68 Gy/25# to prostate, 50 Gy/25# to pelvic nodes, including common iliac) using computerized stratified block randomization, stratified by Gleason score, type of androgen deprivation, prostate-specific antigen at diagnosis, and prior transurethral resection of the prostate. All patients received image-guided, intensity-modulated radiotherapy and minimum 2 years of androgen deprivation therapy. The primary end point was 5-year biochemical failure-free survival (BFFS), and secondary end points were disease-free survival (DFS) and overall survival (OS). RESULTS From November 2011 to August 2017, a total of 224 patients were randomly assigned (PORT = 114, WPRT = 110). At a median follow-up of 68 months, 36 biochemical failures (PORT = 25, WPRT = 7) and 24 deaths (PORT = 13, WPRT = 11) were recorded. Five-year BFFS was 95.0% (95% CI, 88.4 to 97.9) with WPRT versus 81.2% (95% CI, 71.6 to 87.8) with PORT, with an unadjusted hazard ratio (HR) of 0.23 (95% CI, 0.10 to 0.52; P &lt; .0001). WPRT also showed higher 5-year DFS (89.5% v 77.2%; HR, 0.40; 95% CI, 0.22 to 0.73; P = .002), but 5-year OS did not appear to differ (92.5% v 90.8%; HR, 0.92; 95% CI, 0.41 to 2.05; P = .83). Distant metastasis-free survival was also higher with WPRT (95.9% v 89.2%; HR, 0.35; 95% CI, 0.15 to 0.82; P = .01). Benefit in BFFS and DFS was maintained across prognostic subgroups. CONCLUSION Prophylactic pelvic irradiation for high-risk, locally advanced prostate cancer improved BFFS and DFS as compared with PORT, but OS did not appear to differ.

Keratins are cytoplasmic intermediate filament proteins preferentially expressed by epithelial tissues in a site-specific and differentiation-dependent manner. The complex network of keratin filaments in stratified epithelia is tightly regulated during squamous cell differentiation. Keratin 14 (K14) is expressed in mitotically active basal layer cells, along with its partner keratin 5 (K5), and their expression is down-regulated as cells differentiate. Apart from the cytoprotective functions of K14, very little is known about K14 regulatory functions, since the K14 knockout mice show postnatal lethality. In this study, K14 expression was inhibited using RNA interference in cell lines derived from stratified epithelia to study the K14 functions in epithelial homeostasis. The K14 knockdown clones demonstrated substantial decreases in the levels of the K14 partner K5. These cells showed reduction in cell proliferation and delay in cell cycle progression, along with decreased phosphorylated Akt levels. K14 knockdown cells also exhibited enhanced levels of activated Notch1, involucrin, and K1. In addition, K14 knockdown AW13516 cells showed significant reduction in tumorigenicity. Our results suggest that K5 and K14 may have a role in maintenance of cell proliferation potential in the basal layer of stratified epithelia, modulating phosphatidylinositol 3-kinase/Akt-mediated cell proliferation and/or Notch1-dependent cell differentiation.

Curcumin is the lipid-soluble antioxidant compound obtained from the rhizome of Curcuma longa Linn, also known as turmeric. Curcumin targets multiple chemotherapeutic and inflammatory pathways and has demonstrated safety and tolerability in humans, supporting its potential as a therapeutic agent; however, the clinical literature lacks conclusive evidence supporting its use as a therapeutic agent due to its low bioavailability in humans. The purpose of this study was to quantify plasma levels of free curcumin after dosing of a solid lipid curcumin particle (SLCP) formulation versus unformulated curcumin in healthy volunteers and to determine its tolerability and dose-plasma concentration relationship in late-stage osteosarcoma patients. Doses of 2, 3, and 4 g of SLCP were evaluated in 11 patients with osteosarcoma. Plasma curcumin levels were measured using a validated high-performance liquid chromatography method. The limit of detection of the assay was 1 ng/mL of curcumin. In healthy subjects, the mean peak concentration of curcumin achieved from dosing 650 mg of SLCP was 22.43 ng/mL, whereas plasma curcumin from dosing an equal quantity of unformulated 95% curcuminoids extract was not detected. In both healthy individuals and osteosarcoma patients, high interindividual variability in pharmacokinetics and nonlinear dose dependency was observed, suggesting potentially complex absorption kinetics. Overall, good tolerability was noted in both healthy and osteosarcoma groups.

The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA.