Anti-EGFR antibody-drug conjugate carrying an inhibitor targeting CDK restricts triple-negative breast cancer growth.

PURPOSE: Anti-EGFR antibodies show limited response in breast cancer, partly due to activation of compensatory pathways. Furthermore, despite clinical success of CDK4/6 inhibitors in hormone receptor-positive tumors, aggressive triple-negative breast cancers (TNBCs) are largely resistant due to CDK2/cyclin E expression, while free CDK2 inhibitors display normal tissue toxicity, limiting their therapeutic application. A cetuximab-based antibody drug conjugate (ADC) carrying a CDK inhibitor selected based on oncogene dysregulation, alongside patient subgroup stratification, may provide EGFR-targeted delivery. EXPERIMENTAL DESIGN: Expression of G1/S-phase cell cycle regulators were evaluated alongside EGFR in breast cancer. We conjugated cetuximab with CDK inhibitor SNS-032, for specific delivery to EGFR-expressing cells. We assessed ADC internalization, and its anti-tumor functions in vitro and in orthotopically-grown basal-like/TNBC xenografts. RESULTS: Transcriptomic (6173 primary, 27 baseline and matched post-chemotherapy residual tumors), scRNA-seq (150290 cells, 27 treatment-naïve tumors) and spatial transcriptomic (43 tumor sections, 22 TNBCs) analyses confirmed expression of CDK2 and its cyclin partners in basal-like/TNBCs, associated with EGFR. Spatiotemporal live-cell imaging and super-resolution confocal microscopy demonstrated ADC colocalization with late lysosomal clusters. The ADC inhibited cell cycle progression, induced cytotoxicity against high EGFR-expressing tumor cells and bystander killing of neighboring EGFR-low tumor cells, but minimal effects on immune cells. Despite carrying a small fraction of the drug, the ADC restricted EGFR-expressing spheroid and cell line/patient-derived xenograft tumor growth. CONCLUSIONS: Exploiting EGFR overexpression, and dysregulated cell cycle in aggressive and treatment-refractory tumors, a cetuximab-CDK inhibitor ADC may provide selective and efficacious delivery of cell cycle-targeted agents to basal-like/TNBCs, including chemotherapy-resistant residual disease.

A RIPK1-specific PROTAC degrader achieves potent antitumor activity by enhancing immunogenic cell death.

Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) functions as a critical stress sentinel that coordinates cell survival, inflammation, and immunogenic cell death (ICD). Although the catalytic function of RIPK1 is required to trigger cell death, its non-catalytic scaffold function mediates strong pro-survival signaling. Accordingly, cancer cells can hijack RIPK1 to block necroptosis and evade immune detection. We generated a small-molecule proteolysis-targeting chimera (PROTAC) that selectively degraded human and murine RIPK1. PROTAC-mediated depletion of RIPK1 deregulated TNFR1 and TLR3/4 signaling hubs, accentuating the output of NF-κB, MAPK, and IFN signaling. Additionally, RIPK1 degradation simultaneously promoted RIPK3 activation and necroptosis induction. We further demonstrated that RIPK1 degradation enhanced the immunostimulatory effects of radio- and immunotherapy by sensitizing cancer cells to treatment-induced TNF and interferons. This promoted ICD, antitumor immunity, and durable treatment responses. Consequently, targeting RIPK1 by PROTACs emerges as a promising approach to overcome radio- or immunotherapy resistance and enhance anticancer therapies.

Longitudinal Assessment of Tumor-Infiltrating Lymphocytes in Primary Breast Cancer Following Neoadjuvant Radiation Therapy.

PURPOSE: Tumor-infiltrating lymphocytes (TILs) have prognostic significance in several cancers, including breast cancer. Despite interest in combining radiation therapy with immunotherapy, little is known about the effect of radiation therapy itself on the tumor-immune microenvironment, including TILs. Here, we interrogated longitudinal dynamics of TILs and systemic lymphocytes in patient samples taken before, during, and after neoadjuvant radiation therapy (NART) from PRADA and Neo-RT breast clinical trials. METHODS AND MATERIALS: We manually scored stromal TILs (sTILs) from longitudinal tumor samples using standardized guidelines as well as deep learning-based scores at cell-level (cTIL) and cell- and tissue-level combination analyses (SuperTIL). In parallel, we interrogated absolute lymphocyte counts from routine blood tests at corresponding time points during treatment. Exploratory analyses studied the relationship between TILs and pathologic complete response (pCR) and long-term outcomes. RESULTS: Patients receiving NART experienced a significant and uniform decrease in sTILs that did not recover at the time of surgery (P < .0001). This lymphodepletive effect was also mirrored in peripheral blood. Our SuperTIL deep learning score showed good concordance with manual sTILs and importantly performed comparably to manual scores in predicting pCR from diagnostic biopsies. The analysis suggested an association between baseline sTILs and pCR, as well as sTILs at surgery and relapse, in patients receiving NART. CONCLUSIONS: This study provides novel insights into TIL dynamics in the context of NART in breast cancer and demonstrates the potential for artificial intelligence to assist routine pathology. We have identified trends that warrant further interrogation and have a bearing on future radioimmunotherapy trials.

Durable responses to ATR inhibition with ceralasertib in tumors with genomic defects and high inflammation.

BACKGROUNDPhase 1 study of ATRinhibition alone or with radiation therapy (PATRIOT) was a first-in-human phase I study of the oral ATR (ataxia telangiectasia and Rad3-related) inhibitor ceralasertib (AZD6738) in advanced solid tumors.METHODSThe primary objective was safety. Secondary objectives included assessment of antitumor responses and pharmacokinetic (PK) and pharmacodynamic (PD) studies. Sixty-seven patients received 20-240 mg ceralasertib BD continuously or intermittently (14 of a 28-day cycle).RESULTSIntermittent dosing was better tolerated than continuous, which was associated with dose-limiting hematological toxicity. The recommended phase 2 dose of ceralasertib was 160 mg twice daily for 2 weeks in a 4-weekly cycle. Modulation of target and increased DNA damage were identified in tumor and surrogate PD. There were 5 (8%) confirmed partial responses (PRs) (40-240 mg BD), 34 (52%) stable disease (SD), including 1 unconfirmed PR, and 27 (41%) progressive disease. Durable responses were seen in tumors with loss of AT-rich interactive domain-containing protein 1A (ARID1A) and DNA damage-response defects. Treatment-modulated tumor and systemic immune markers and responding tumors were more immune inflamed than nonresponding.CONCLUSIONCeralasertib monotherapy was tolerated at 160 mg BD intermittently and associated with antitumor activity.TRIAL REGISTRATIONClinicaltrials.gov: NCT02223923, EudraCT: 2013-003994-84.FUNDINGCancer Research UK, AstraZeneca, UK Department of Health (National Institute for Health Research), Rosetrees Trust, Experimental Cancer Medicine Centre.

Genomic profiling and pre-clinical modelling of breast cancer leptomeningeal metastasis reveals acquisition of a lobular-like phenotype.

Breast cancer leptomeningeal metastasis (BCLM), where tumour cells grow along the lining of the brain and spinal cord, is a devastating development for patients. Investigating this metastatic site is hampered by difficulty in accessing tumour material. Here, we utilise cerebrospinal fluid (CSF) cell-free DNA (cfDNA) and CSF disseminated tumour cells (DTCs) to explore the clonal evolution of BCLM and heterogeneity between leptomeningeal and extracranial metastatic sites. Somatic alterations with potential therapeutic actionability were detected in 81% (17/21) of BCLM cases, with 19% detectable in CSF cfDNA only. BCLM was enriched in genomic aberrations in adherens junction and cytoskeletal genes, revealing a lobular-like breast cancer phenotype. CSF DTCs were cultured in 3D to establish BCLM patient-derived organoids, and used for the successful generation of BCLM in vivo models. These data reveal that BCLM possess a unique genomic aberration profile and highlight potential cellular dependencies in this hard-to-treat form of metastatic disease.

Integrated Multimodal Analyses of DNA Damage Response and Immune Markers as Predictors of Response in Metastatic Triple-Negative Breast Cancer in the TNT Trial (NCT00532727).

PURPOSE: The TNT trial (NCT00532727) showed no evidence of carboplatin superiority over docetaxel in metastatic triple-negative breast cancer (mTNBC), but carboplatin benefit was observed in the germline BRCA1/2 mutation subgroup. Broader response-predictive biomarkers are needed. We explored the predictive ability of DNA damage response (DDR) and immune markers. EXPERIMENTAL DESIGN: Tumor-infiltrating lymphocytes were evaluated for 222 of 376 patients. Primary tumors (PT) from 186 TNT participants (13 matched recurrences) were profiled using total RNA sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective response rate (ORR) and progression-free survival (PFS). Conditional inference forest clustering was applied to integrate multimodal data. The biology of subgroups was characterized by 693 gene expression modules and other markers. RESULTS: Transcriptional DDR-related biomarkers were not predictive of ORR to either treatment overall. Changes from PT to recurrence were demonstrated; in chemotherapy-naïve patients, transcriptional DDR markers separated carboplatin responders from nonresponders (P values = 0.017; 0.046). High immune infiltration was associated with docetaxel ORR (interaction P values < 0.05). Six subgroups were identified; the immune-enriched cluster had preferential docetaxel response [62.5% (D) vs. 29.4% (C); P = 0.016]. The immune-depleted cluster had preferential carboplatin response [8.0% (D) vs. 40.0% (C); P = 0.011]. DDR-related subgroups were too small to assess ORR. CONCLUSIONS: High immune features predict docetaxel response, and high DDR signature scores predict carboplatin response in treatment-naïve mTNBC. Integrating multimodal DDR and immune-related markers identifies subgroups with differential treatment sensitivity. Treatment options for patients with immune-low and DDR-proficient tumors remains an outstanding need. Caution is needed using PT-derived transcriptional signatures to direct treatment in mTNBC, particularly DDR-related markers following prior chemotherapy.

SF3B1 hotspot mutations confer sensitivity to PARP inhibition by eliciting a defective replication stress response.

SF3B1 hotspot mutations are associated with a poor prognosis in several tumor types and lead to global disruption of canonical splicing. Through synthetic lethal drug screens, we identify that SF3B1 mutant (SF3B1MUT) cells are selectively sensitive to poly (ADP-ribose) polymerase inhibitors (PARPi), independent of hotspot mutation and tumor site. SF3B1MUT cells display a defective response to PARPi-induced replication stress that occurs via downregulation of the cyclin-dependent kinase 2 interacting protein (CINP), leading to increased replication fork origin firing and loss of phosphorylated CHK1 (pCHK1; S317) induction. This results in subsequent failure to resolve DNA replication intermediates and G2/M cell cycle arrest. These defects are rescued through CINP overexpression, or further targeted by a combination of ataxia-telangiectasia mutated and PARP inhibition. In vivo, PARPi produce profound antitumor effects in multiple SF3B1MUT cancer models and eliminate distant metastases. These data provide the rationale for testing the clinical efficacy of PARPi in a biomarker-driven, homologous recombination proficient, patient population.

Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.

Background: Intracellular communication within the tumour is complex and extracellular vesicles (EVs) have been identified as major contributing factors for the cell-to-cell communication in the local and distant tumour environments. Here, we examine the differential effects of breast cancer (BC) subtype-specific patient serum and cell-line derived EVs in the regulation of T cell mediated immune responses. Methods: Ultracentrifugation was used to isolate EVs from sera of 63 BC patients, 15 healthy volunteers and 4 human breast cancer cell lines. Longitudinal blood draws for EV isolation for patients on neoadjuvant chemotherapy was also performed. Characterization of EVs was performed by Nanoparticle Tracking Analysis (NTA), transmission electron microscopy (TEM) and immunoblotting. CD63 staining was performed on a tissue microarray of 218 BC patients. In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. In vitro stimulation of PBMCs with EVs from serum and cell-line derived EVs was performed and changes in the immune phenotypes characterized by flow cytometry. Cytokine profiles were assessed using a 105-plex immunoassay or IL10 ELISA. Results: Patients with triple negative breast cancers (TNBCs) exhibited the lowest number of EVs in the sera; whilst the highest was detected in ER+HER2+ cancers; reflected also in the higher level of CD63+ vesicles found within the ER+HER2+ local tumour microenvironment. Transcriptomic analysis of the TCGA data identified that samples assigned with lower EV scores had significantly higher abundance of CD4+ memory activated T cells, T follicular cells and CD8 T cells, plasma, and memory B cells; whilst samples with high EV scores were more enriched for anti-inflammatory M2 macrophages and mast cells. A negative correlation between EV expression scores and stromal TIL counts was also observed. In vitro experiments confirmed that circulating EVs within breast cancer subtypes have functionally differing immunomodulatory capabilities, with EVs from patients with the most aggressive breast cancer subtype (TNBCs) demonstrating the most immune-suppressive phenotype (decreased CD3+HLA-DR+ but increased CD3+PD-L1 T cells, increased CD4+CD127-CD25hi T regulatory cells with associated increase in IL10 cytokine production). In depth assessment of the cytokine modulation triggered by the serum/cell line derived exosomes confirmed differential inflammatory cytokine profiles across differing breast cancer subtypes. Studies using the MDA-231 TNBC breast cancer cell-line derived EVs provided further support that TNBC EVs induced the most immunosuppressive response within PBMCs. Discussion: Our study supports further investigations into how tumour derived EVs are a mechanism that cancers can exploit to promote immune suppression; and breast cancer subtypes produce EVs with differing immunomodulatory capabilities. Understanding the intracellular/extracellular pathways implicated in alteration from active to suppressed immune state may provide a promising way forward for restoring immune competence in specific breast cancer patient populations.

Next-Generation Sequencing and Image-Guided Tissue Sampling: A Primer for Interventional Radiologists.

The discovery of increasing numbers of actionable molecular and gene targets for cancer treatment has driven the demand for tissue sampling for next-generation sequencing (NGS). Requirements for sequencing can be very specific, and inadequate sampling leads to delays in management and decision making. It is important that interventional radiologists are aware of NGS technologies and their common applications and be cognizant of the factors that contribute to successful sample sequencing. This review summarizes the fundamentals of cancer tissue collection and processing for NGS. It elaborates on sequencing technologies and their applications with the aim of providing readers with a working understanding that can enhance their clinical practice. It then describes imaging, tumor, biopsy, and sample collection factors that improve the chances of NGS success. Finally, it discusses future practice, highlighting the problem of undersampling in both clinical and research settings and the opportunities within interventional radiology to address this.

Dynamic Changes in the NK-, Neutrophil-, and B-cell Immunophenotypes Relevant in High Metastatic Risk Post Neoadjuvant Chemotherapy-Resistant Early Breast Cancers.

PURPOSE: To identify potential immune targets in post-neoadjuvant chemotherapy (NAC)-resistant triple-negative breast cancer (TNBC) and ER+HER2- breast cancer disease. EXPERIMENTAL DESIGN: Following pathology review, 153 patients were identified as having residual cancer burden (RCB) II/III disease (TNBC n = 80; ER+HER2-n = 73). Baseline pre-NAC samples were available for evaluation for 32 of 80 TNBC and 36 of 73 ER+HER2- cases. Bright-field hematoxylin and eosin assessment allowed for tumor-infiltrating lymphocyte (TIL) evaluation in all cases. Multiplexed immunofluorescence was used to identify the abundance and distribution of immune cell subsets. Levels of checkpoints including PD-1/PD-L1 expression were also quantified. Findings were then validated using expression profiling of cancer and immune-related genes. Cytometry by time-of-flight characterized the dynamic changes in circulating immune cells with NAC. RESULTS: RCB II/III TNBC and ER+HER2- breast cancer were immunologically "cold" at baseline and end of NAC. Although the distribution of immune cell subsets across subtypes was similar, the mRNA expression profiles were both subtype- and chemotherapy-specific. TNBC RCB II/III disease was enriched with genes related to neutrophil degranulation, and displayed strong interplay across immune and cancer pathways. We observed similarities in the dynamic changes in B-cell biology following NAC irrespective of subtype. However, NAC induced changes in the local and circulating tumor immune microenvironment (TIME) that varied by subtype and response. Specifically, in TNBC residual disease, we observed downregulation of stimulatory (CD40/OX40L) and inhibitory (PD-L1/PD-1) receptor expression and an increase in NK cell populations (especially non-cytolytic, exhausted CD56dimCD16-) within both the local TIME and peripheral white cell populations. CONCLUSIONS: This study identifies several potential immunologic pathways in residual disease, which may be targeted to benefit high-risk patients.

Rates and Outcomes of Breast Lesions of Uncertain Malignant Potential (B3) benchmarked against the National Breast Screening Pathology Audit; Improving Performance in a High Volume Screening Unit.

INTRODUCTION: Our breast screening unit was identified as high outlier for B3 lesions with a low positive predictive value (PPV) compared to the England average. This prompted a detailed internal audit and review of B3 lesions and their outcomes to identify causes and address any variation in practice. PATIENTS AND METHODS: The B3 rate was calculated in 4168 breast core biopsies from 2019, using the subsequent excision to determine the PPV. Atypical intraductal epithelial proliferation (AIDEP) cases were subject to microscopic review to reassess the presence of atypia against published criteria. The B3 rate was re-audited in 2021, and the results compared. RESULTS: Screening cases had a high B3 rate of 12.4% (30% above the national average), and a PPV of 7.7% (9.7% with atypia). AIDEP was identified as a possible cause of this outlier status. On review and by consensus, AIDEP was confirmed in only 66% of cases reported as such, 17% were downgraded, and 16% did not reach consensus, the latter highlighting the difficulty and subjectivity in diagnosis of these lesions. Repeat audit of B3 rates after this extended review revealed a reduction from 12.4% to 9.11%, which is more in line with national standards. CONCLUSION: Benchmarking against national reporting standards is critical for service improvement. Through a supportive environment, team working, rigorous internal review and adherence to guidelines, interobserver variation and outlier status in breast pathology screening outliers can both be addressed. This study can serve as a model to other outlier units to identify and tackle underlying causes.

Assessment of the Molecular Heterogeneity of E-Cadherin Expression in Invasive Lobular Breast Cancer.

Mutations and loss of E-cadherin protein expression define the vast majority of invasive lobular carcinomas. In a subset of these cases, the heterogeneous expression of E-cadherin is observed either as wild-type (strong membranous) expression or aberrant expression (cytoplasmic expression). However, it is unclear as to whether the two components would be driven by distinct genetic or epigenetic alterations. Here, we used whole genome DNA sequencing and methylation array profiling of two separately dissected components of nine invasive lobular carcinomas with heterogeneous E-cadherin expression. E-cadherin negative and aberrant/positive components of E-cadherin heterogeneous tumours showed a similar mutational, copy number and promoter methylation repertoire, suggesting they arise from a common ancestor, as opposed to the collision of two independent tumours. We found that the majority of E-cadherin heterogeneous tumours harboured CDH1 mutations in both the E-cadherin negative and aberrant/positive components together with somatic mutations in additional driver genes known to be enriched in both pure invasive carcinomas of no special type and invasive lobular breast cancers, whereas these were less commonly observed in CDH1 wild-type tumours. CDH1 mutant tumours also exhibited a higher mutation burden as well as increased presence of APOBEC-dependent mutational signatures 2 and 13 compared to CDH1 wild-type tumours. Together, our results suggest that regardless of E-cadherin protein expression, tumours showing heterogeneous expression of E-cadherin should be considered as part of the spectrum of invasive lobular breast cancers.

ADGRL4/ELTD1 Expression in Breast Cancer Cells Induces Vascular Normalization and Immune Suppression.

ELTD1/ADGRL4 expression is increased in the vasculature of a number of tumor types and this correlates with a good prognosis. Expression has also been reported in some tumor cells with high expression correlating with a good prognosis in hepatocellular carcinoma (HCC) and a poor prognosis in glioblastoma. Here we show that 35% of primary human breast tumors stain positively for ELTD1, with 9% having high expression that correlates with improved relapse-free survival. Using immunocompetent, syngeneic mouse breast cancer models we found that tumors expressing recombinant murine Eltd1 grew faster than controls, with an enhanced ability to metastasize and promote systemic immune effects. The Eltd1-expressing tumors had larger and better perfused vessels and tumor-endothelial cell interaction led to the release of proangiogenic and immune-modulating factors. M2-like macrophages increased in the stroma along with expression of programmed death-ligand 1 (PD-L1) on tumor and immune cells, to create an immunosuppressive microenvironment that allowed Eltd1-regulated tumor growth in the presence of an NY-ESO-1-specific immune response. Eltd1-positive tumors also responded better to chemotherapy which could explain the relationship to a good prognosis observed in primary human cases. Thus, ELTD1 expression may enhance delivery of therapeutic antibodies to reverse the immunosuppression and increase response to chemotherapy and radiotherapy in this subset of tumors. ELTD1 may be useful as a selection marker for such therapies. IMPLICATIONS: ELTD1 expression in mouse breast tumors creates an immunosuppressive microenvironment and increases vessel size and perfusion. Its expression may enhance the delivery of therapies targeting the immune system.

Quantitative Assessment and Prognostic Associations of the Immune Landscape in Ovarian Clear Cell Carcinoma.

Ovarian clear cell carcinoma (OCCC) is a rare subtype of epithelial ovarian cancer characterised by a high frequency of loss-of-function ARID1A mutations and a poor response to chemotherapy. Despite their generally low mutational burden, an intratumoural T cell response has been reported in a subset of OCCC, with ARID1A purported to be a biomarker for the response to the immune checkpoint blockade independent of micro-satellite instability (MSI). However, assessment of the different immune cell types and spatial distribution specifically within OCCC patients has not been described to date. Here, we characterised the immune landscape of OCCC by profiling a cohort of 33 microsatellite stable OCCCs at the genomic, gene expression and histological level using targeted sequencing, gene expression profiling using the NanoString targeted immune panel, and multiplex immunofluorescence to assess the spatial distribution and abundance of immune cell populations at the protein level. Analysis of these tumours and subsequent independent validation identified an immune-related gene expression signature associated with risk of recurrence of OCCC. Whilst histological quantification of tumour-infiltrating lymphocytes (TIL, Salgado scoring) showed no association with the risk of recurrence or ARID1A mutational status, the characterisation of TILs via multiplexed immunofluorescence identified spatial differences in immunosuppressive cell populations in OCCC. Tumour-associated macrophages (TAM) and regulatory T cells were excluded from the vicinity of tumour cells in low-risk patients, suggesting that high-risk patients have a more immunosuppressive microenvironment. We also found that TAMs and cytotoxic T cells were also excluded from the vicinity of tumour cells in ARID1A-mutated OCCCs compared to ARID1A wild-type tumours, suggesting that the exclusion of these immune effectors could determine the host response of ARID1A-mutant OCCCs to therapy. Overall, our study has provided new insights into the immune landscape and prognostic associations in OCCC and suggest that tailored immunotherapeutic approaches may be warranted for different subgroups of OCCC patients.

Ubiquitylation of MLKL at lysine 219 positively regulates necroptosis-induced tissue injury and pathogen clearance.

Necroptosis is a lytic, inflammatory form of cell death that not only contributes to pathogen clearance but can also lead to disease pathogenesis. Necroptosis is triggered by RIPK3-mediated phosphorylation of MLKL, which is thought to initiate MLKL oligomerisation, membrane translocation and membrane rupture, although the precise mechanism is incompletely understood. Here, we show that K63-linked ubiquitin chains are attached to MLKL during necroptosis and that ubiquitylation of MLKL at K219 significantly contributes to the cytotoxic potential of phosphorylated MLKL. The K219R MLKL mutation protects animals from necroptosis-induced skin damage and renders cells resistant to pathogen-induced necroptosis. Mechanistically, we show that ubiquitylation of MLKL at K219 is required for higher-order assembly of MLKL at membranes, facilitating its rupture and necroptosis. We demonstrate that K219 ubiquitylation licenses MLKL activity to induce lytic cell death, suggesting that necroptotic clearance of pathogens as well as MLKL-dependent pathologies are influenced by the ubiquitin-signalling system.

Artificial intelligence and digital pathology: Opportunities and implications for immuno-oncology.

The field of immuno-oncology has expanded rapidly over the past decade, but key questions remain. How does tumour-immune interaction regulate disease progression? How can we prospectively identify patients who will benefit from immunotherapy? Identifying measurable features of the tumour immune-microenvironment which have prognostic or predictive value will be key to making meaningful gains in these areas. Recent developments in deep learning enable big-data analysis of pathological samples. Digital approaches allow data to be acquired, integrated and analysed far beyond what is possible with conventional techniques, and to do so efficiently and at scale. This has the potential to reshape what can be achieved in terms of volume, precision and reliability of output, enabling data for large cohorts to be summarised and compared. This review examines applications of artificial intelligence (AI) to important questions in immuno-oncology (IO). We discuss general considerations that need to be taken into account before AI can be applied in any clinical setting. We describe AI methods that have been applied to the field of IO to date and present several examples of their use.

A FIJI macro for quantifying pattern in extracellular matrix.

Diverse extracellular matrix patterns are observed in both normal and pathological tissue. However, most current tools for quantitative analysis focus on a single aspect of matrix patterning. Thus, an automated pipeline that simultaneously quantifies a broad range of metrics and enables a comprehensive description of varied matrix patterns is needed. To this end, we have developed an ImageJ plugin called TWOMBLI, which stands for The Workflow Of Matrix BioLogy Informatics. This pipeline includes metrics of matrix alignment, length, branching, end points, gaps, fractal dimension, curvature, and the distribution of fibre thickness. TWOMBLI is designed to be quick, versatile and easy-to-use particularly for non-computational scientists. TWOMBLI can be downloaded from https://github.com/wershofe/TWOMBLI together with detailed documentation and tutorial video. Although developed with the extracellular matrix in mind, TWOMBLI is versatile and can be applied to vascular and cytoskeletal networks. Here we present an overview of the pipeline together with examples from a wide range of contexts where matrix patterns are generated.

3D Functional Genomics Screens Identify CREBBP as a Targetable Driver in Aggressive Triple-Negative Breast Cancer.

Triple-negative breast cancers (TNBC) are resistant to standard-of-care chemotherapy and lack known targetable driver gene alterations. Identification of novel drivers could aid the discovery of new treatment strategies for this hard-to-treat patient population, yet studies using high-throughput and accurate models to define the functions of driver genes in TNBC to date have been limited. Here, we employed unbiased functional genomics screening of the 200 most frequently mutated genes in breast cancer, using spheroid cultures to model in vivo-like conditions, and identified the histone acetyltransferase CREBBP as a novel tumor suppressor in TNBC. CREBBP protein expression in patient tumor samples was absent in 8% of TNBCs and at a high frequency in other tumors, including squamous lung cancer, where CREBBP-inactivating mutations are common. In TNBC, CREBBP alterations were associated with higher genomic heterogeneity and poorer patient survival and resulted in upregulation and dependency on a FOXM1 proliferative program. Targeting FOXM1-driven proliferation indirectly with clinical CDK4/6 inhibitors (CDK4/6i) selectively impaired growth in spheroids, cell line xenografts, and patient-derived models from multiple tumor types with CREBBP mutations or loss of protein expression. In conclusion, we have identified CREBBP as a novel driver in aggressive TNBC and identified an associated genetic vulnerability in tumor cells with alterations in CREBBP and provide a preclinical rationale for assessing CREBBP alterations as a biomarker of CDK4/6i response in a new patient population. SIGNIFICANCE: This study demonstrates that CREBBP genomic alterations drive aggressive TNBC, lung cancer, and lymphomas and may be selectively treated with clinical CDK4/6 inhibitors.

RIPK1-mediated immunogenic cell death promotes anti-tumour immunity against soft-tissue sarcoma.

Drugs that mobilise the immune system against cancer are dramatically improving care for many people. Dying cancer cells play an active role in inducing anti-tumour immunity but not every form of death can elicit an immune response. Moreover, resistance to apoptosis is a major problem in cancer treatment and disease control. While the term "immunogenic cell death" is not fully defined, activation of receptor-interacting serine/threonine-protein kinase 1 (RIPK1) can induce a type of death that mobilises the immune system against cancer. However, no clinical treatment protocols have yet been established that would harness the immunogenic potential of RIPK1. Here, we report the first pre-clinical application of an in vivo treatment protocol for soft-tissue sarcoma that directly engages RIPK1-mediated immunogenic cell death. We find that RIPK1-mediated cell death significantly improves local disease control, increases activation of CD8+ T cells as well as NK cells, and enhances the survival benefit of immune checkpoint blockade. Our findings warrant a clinical trial to assess the survival benefit of RIPK1-induced cell death in patients with advanced disease at limb extremities.

SuperHistopath: A Deep Learning Pipeline for Mapping Tumor Heterogeneity on Low-Resolution Whole-Slide Digital Histopathology Images.

High computational cost associated with digital pathology image analysis approaches is a challenge towards their translation in routine pathology clinic. Here, we propose a computationally efficient framework (SuperHistopath), designed to map global context features reflecting the rich tumor morphological heterogeneity. SuperHistopath efficiently combines i) a segmentation approach using the linear iterative clustering (SLIC) superpixels algorithm applied directly on the whole-slide images at low resolution (5x magnification) to adhere to region boundaries and form homogeneous spatial units at tissue-level, followed by ii) classification of superpixels using a convolution neural network (CNN). To demonstrate how versatile SuperHistopath was in accomplishing histopathology tasks, we classified tumor tissue, stroma, necrosis, lymphocytes clusters, differentiating regions, fat, hemorrhage and normal tissue, in 127 melanomas, 23 triple-negative breast cancers, and 73 samples from transgenic mouse models of high-risk childhood neuroblastoma with high accuracy (98.8%, 93.1% and 98.3% respectively). Furthermore, SuperHistopath enabled discovery of significant differences in tumor phenotype of neuroblastoma mouse models emulating genomic variants of high-risk disease, and stratification of melanoma patients (high ratio of lymphocyte-to-tumor superpixels (p = 0.015) and low stroma-to-tumor ratio (p = 0.028) were associated with a favorable prognosis). Finally, SuperHistopath is efficient for annotation of ground-truth datasets (as there is no need of boundary delineation), training and application (~5 min for classifying a whole-slide image and as low as ~30 min for network training). These attributes make SuperHistopath particularly attractive for research in rich datasets and could also facilitate its adoption in the clinic to accelerate pathologist workflow with the quantification of phenotypes, predictive/prognosis markers.