Association Between Time From Surgery to Radiation Therapy and Multimodality Treatment Outcomes in HPV+ Head and Neck Cancer: A Multi-Institutional Cohort Experience.

Purpose: Oropharyngeal squamous cell cancers (OPSCCs) are traditionally managed with surgery and, if indicated, adjuvant radiation therapy (RT) with or without chemotherapy. NCCN recommends keeping the time from surgery to the start of RT (TSRT) within 6 weeks to avoid possibly compromising patient outcomes. HPV+ OPSCCs behave more favorably than HPV- OPSCCs. We hypothesized that TSRT beyond 6 weeks may not portend poorer outcomes for the former. Methods: We identified nonmetastatic, high-risk HPV+ OPSCCs treated with multimodal therapy at 2 institutions. Prolonged TSRT was defined as >6 weeks and was evaluated for association with recurrence-free survival (RFS). Radiation treatment time (RTT; time from the first to the last day of RT), total treatment package time (TTPT; time from surgery to the end of adjuvant treatments), de-escalated RT (dose ≤56 Gy), concurrent chemotherapy, smoking history, and treatment institution were evaluated as possible confounders. Results: In total, 96 patients were included. The median follow-up time was 62 months (4-123 months); 69 patients underwent transoral robotic surgeries, and 27 received open surgeries. The median postoperative RT dose was 60 Gy (50-70.8 Gy). The median TSRT, RTT, and TTPT were 38 days (11-208), 43 days (26-56 days), and 81 days (40-255 days), respectively. Ten patients failed treatment at a median of 8 months (4-64 months). Two locoregional and 4 distant failures occurred in the group without prolonged TSRT, whereas 2 locoregional and 2 distant failures were recorded in the prolonged TSRT group. Prolonged TTPT, de-escalated RT, chemotherapy, smoking history, and treatment institution were not associated with treatment failure. RTT was dropped from our analyses as no events appeared in the prolonged RTT group, and no reliable hazard ratio could be computed. Conclusions: TSRT > 6 weeks was not significantly associated with inferior outcomes in the postoperative management of HPV+ OPSCCs. Longer TSRT may facilitate better recovery from surgical toxicity, as needed, without compromising oncologic outcomes. The TSRT goal for these cancers should be investigated in future studies.

Analysis of 3D pathology samples using weakly supervised AI.

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.

Long-Term Outcomes of Surgery and Radiation Treatment for Adult Patients with Craniopharyngioma.

OBJECTIVE: Treatment of craniopharyngioma typically entails gross total resection (GTR) or subtotal resection with adjuvant radiation (STR-RT). We analyzed outcomes in adults with craniopharyngioma undergoing GTR versus STR-RT. METHODS: This retrospective study enrolled 115 patients with craniopharyngioma in 5 institutions. Patients with STR received postoperative RT with stereotactic radiosurgery or fractionated radiation therapy per institutional preference and ability to spare optic structures. RESULTS: Median age was 44 years (range, 19-79 years). GTR was performed in 34 patients and STR-RT was performed in 81 patients with median follow-up of 78.9 months (range, 1-268 months). For GTR, local control was 90.5% at 2 years, 87.2% at 3 years, and 71.9% at 5 years. For STR-RT, local control was 93.6% at 2 years, 90.3% at 3 years, and 88.4% at 5 years. At 5 years following resection, there was no difference in local control (P = 0.08). Differences in rates of visual deterioration or panhypopituitarism were not observed between GTR and STR-RT groups. There was no difference in local control in adamantinomatous and papillary craniopharyngioma regardless of treatment. Additionally, worse local control was found in patients receiving STR-RT who were underdosed with fractionated radiation therapy (P = 0.03) or stereotactic radiosurgery (P = 0.04). CONCLUSIONS: Good long-term control was achieved in adults with craniopharyngioma who underwent STR-RT or GTR with no significant difference in local control. First-line treatment for craniopharyngioma should continue to be maximal safe resection followed by RT as needed to balance optimal local control with long-term morbidity.

Demographic bias in misdiagnosis by computational pathology models.

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas. For example, when using common modeling approaches, we observed performance gaps (in area under the receiver operating characteristic curve) between white and Black patients of 3.0% for breast cancer subtyping, 10.9% for lung cancer subtyping and 16.0% for IDH1 mutation prediction in gliomas. We found that richer feature representations obtained from self-supervised vision foundation models reduce performance variations between groups. These representations provide improvements upon weaker models even when those weaker models are combined with state-of-the-art bias mitigation strategies and modeling choices. Nevertheless, self-supervised vision foundation models do not fully eliminate these discrepancies, highlighting the continuing need for bias mitigation efforts in computational pathology. Finally, we demonstrate that our results extend to other demographic factors beyond patient race. Given these findings, we encourage regulatory and policy agencies to integrate demographic-stratified evaluation into their assessment guidelines.

Towards a general-purpose foundation model for computational pathology.

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks, requiring the objective characterization of histopathological entities from whole-slide images (WSIs). The high resolution of WSIs and the variability of morphological features present significant challenges, complicating the large-scale annotation of data for high-performance applications. To address this challenge, current efforts have proposed the use of pretrained image encoders through transfer learning from natural image datasets or self-supervised learning on publicly available histopathology datasets, but have not been extensively developed and evaluated across diverse tissue types at scale. We introduce UNI, a general-purpose self-supervised model for pathology, pretrained using more than 100 million images from over 100,000 diagnostic H&E-stained WSIs (>77 TB of data) across 20 major tissue types. The model was evaluated on 34 representative CPath tasks of varying diagnostic difficulty. In addition to outperforming previous state-of-the-art models, we demonstrate new modeling capabilities in CPath such as resolution-agnostic tissue classification, slide classification using few-shot class prototypes, and disease subtyping generalization in classifying up to 108 cancer types in the OncoTree classification system. UNI advances unsupervised representation learning at scale in CPath in terms of both pretraining data and downstream evaluation, enabling data-efficient artificial intelligence models that can generalize and transfer to a wide range of diagnostically challenging tasks and clinical workflows in anatomic pathology.

Developmental role of macrophages modeled in human pluripotent stem cell-derived intestinal tissue.

Macrophages populate the embryo early in gestation, but their role in development is not well defined. In particular, specification and function of macrophages in intestinal development remain little explored. To study this event in the human developmental context, we derived and combined human intestinal organoid and macrophages from pluripotent stem cells. Macrophages migrate into the organoid, proliferate, and occupy the emerging microanatomical niches of epithelial crypts and ganglia. They also acquire a transcriptomic profile similar to that of fetal intestinal macrophages and display tissue macrophage behaviors, such as recruitment to tissue injury. Using this model, we show that macrophages reduce glycolysis in mesenchymal cells and limit tissue growth without affecting tissue architecture, in contrast to the pro-growth effect of enteric neurons. In short, we engineered an intestinal tissue model populated with macrophages, and we suggest that resident macrophages contribute to the regulation of metabolism and growth of the developing intestine.

A General-Purpose Self-Supervised Model for Computational Pathology.

Tissue phenotyping is a fundamental computational pathology (CPath) task in learning objective characterizations of histopathologic biomarkers in anatomic pathology. However, whole-slide imaging (WSI) poses a complex computer vision problem in which the large-scale image resolutions of WSIs and the enormous diversity of morphological phenotypes preclude large-scale data annotation. Current efforts have proposed using pretrained image encoders with either transfer learning from natural image datasets or self-supervised pretraining on publicly-available histopathology datasets, but have not been extensively developed and evaluated across diverse tissue types at scale. We introduce UNI, a general-purpose self-supervised model for pathology, pretrained using over 100 million tissue patches from over 100,000 diagnostic haematoxylin and eosin-stained WSIs across 20 major tissue types, and evaluated on 33 representative CPath clinical tasks in CPath of varying diagnostic difficulties. In addition to outperforming previous state-of-the-art models, we demonstrate new modeling capabilities in CPath such as resolution-agnostic tissue classification, slide classification using few-shot class prototypes, and disease subtyping generalization in classifying up to 108 cancer types in the OncoTree code classification system. UNI advances unsupervised representation learning at scale in CPath in terms of both pretraining data and downstream evaluation, enabling data-efficient AI models that can generalize and transfer to a gamut of diagnostically-challenging tasks and clinical workflows in anatomic pathology.

Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples.

Human tissue consists of complex structures that display a diversity of morphologies, forming a tissue microenvironment that is, by nature, three-dimensional (3D). However, the current standard-of-care involves slicing 3D tissue specimens into two-dimensional (2D) sections and selecting a few for microscopic evaluation1,2, with concomitant risks of sampling bias and misdiagnosis3-6. To this end, there have been intense efforts to capture 3D tissue morphology and transition to 3D pathology, with the development of multiple high-resolution 3D imaging modalities7-18. However, these tools have had little translation to clinical practice as manual evaluation of such large data by pathologists is impractical and there is a lack of computational platforms that can efficiently process the 3D images and provide patient-level clinical insights. Here we present Modality-Agnostic Multiple instance learning for volumetric Block Analysis (MAMBA), a deep-learning-based platform for processing 3D tissue images from diverse imaging modalities and predicting patient outcomes. Archived prostate cancer specimens were imaged with open-top light-sheet microscopy12-14 or microcomputed tomography15,16 and the resulting 3D datasets were used to train risk-stratification networks based on 5-year biochemical recurrence outcomes via MAMBA. With the 3D block-based approach, MAMBA achieves an area under the receiver operating characteristic curve (AUC) of 0.86 and 0.74, superior to 2D traditional single-slice-based prognostication (AUC of 0.79 and 0.57), suggesting superior prognostication with 3D morphological features. Further analyses reveal that the incorporation of greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, suggesting that there is value in capturing larger extents of spatially heterogeneous 3D morphology. With the rapid growth and adoption of 3D spatial biology and pathology techniques by researchers and clinicians, MAMBA provides a general and efficient framework for 3D weakly supervised learning for clinical decision support and can help to reveal novel 3D morphological biomarkers for prognosis and therapeutic response.

Emerging data on thrombopoietin receptor agonists for management of chemotherapy-induced thrombocytopenia.

INTRODUCTION: Chemotherapy-induced thrombocytopenia (CIT) is a common complication of cancer treatment, frequently leading to reduced relative dose intensity, and is associated with reduced survival. Given the lack of FDA-approved therapies for CIT, thrombopoietin receptor agonists (TPO-RAs) have received significant attention for treatment and prevention of CIT. AREAS COVERED: This review will summarize the development of prior agents for treatment of CIT, discuss the existing literature investigating the use of TPO-RAs in CIT primarily in patients with solid tumor malignancies, and offer insights on the future direction of TPO-RAs and other therapeutics for CIT. EXPERT OPINION: In alignment with NCCN guidelines, we recommend that patients with CIT participate in a clinical trial for consideration of TPO-RA treatment or consider off-label use of romiplostim when participation in clinical trials is not possible. The literature to date supports the use of TPO-RAs for treatment of persistent CIT. Further data is needed to describe the long-term efficacy, safety, and prescribing practices of TPO-RAs in a diverse patient population with a variety of tumor types and chemotherapy regimens in addition to exploring the underlying biology of CIT.

Investigating Morphologic Correlates of Driver Gene Mutation Heterogeneity via Deep Learning.

Despite the crucial role of phenotypic and genetic intratumoral heterogeneity in understanding and predicting clinical outcomes for patients with cancer, computational pathology studies have yet to make substantial steps in this area. The major limiting factor has been the bulk gene-sequencing practice that results in loss of spatial information of gene status, making the study of intratumoral heterogeneity difficult. In this issue of Cancer Research, Acosta and colleagues used deep learning to study if localized gene mutation status can be predicted from localized tumor morphology for clear cell renal cell carcinoma. The algorithm was developed using curated sets of matched hematoxylin and eosin and IHC images, which represent spatially resolved morphology and genotype, respectively. This study confirms the existence of a strong link between morphology and underlying genetics on a regional level, paving the way for further investigations into intratumoral heterogeneity. See related article by Acosta et al., p. 2792.

Systemic bevacizumab as salvage therapy for persistent severe bleeding and anemia in heyde syndrome following aortic valve replacement.

Heyde syndrome is characterized by the co-occurrence of aortic stenosis and bleeding gastrointestinal angiodysplasias, often with acquired von Willebrand syndrome. Current management for bleeding includes hematologic support with red cell transfusion and intravenous iron and correction of aortic stenosis with valve replacement. However, persistent Heyde syndrome after valve replacement occurs in a significant minority of cases, and there is no accepted therapy for these patients. Given that the pathophysiology of angiodysplasia formation in Heyde syndrome involves dysregulated angiogenesis, targeting angiogenesis may be an effective therapeutic option. We describe two cases of persistent Heyde syndrome with severe bleeding and anemia in patients following aortic valve replacement who were treated with systemic bevacizumab, a monoclonal antibody directed against vascular endothelial growth factor. In both cases, treatment was successful, with resolution of bleeding, liberation from hematologic support, and normalization of hemoglobin. In addition to responding to therapy, neither patient had treatment-related adverse events (and both had recurrent anemia upon treatment discontinuation, further evidence of the therapeutic impact of bevacizumab). Additional investigation into the use of systemic antiangiogenic therapy for treatment of Heyde syndrome is warranted.

Scalp-Sparing Radiation With Concurrent Temozolomide and Tumor Treating Fields (SPARE) for Patients With Newly Diagnosed Glioblastoma.

Introduction: Standard-of-care treatment for patients with newly diagnosed glioblastoma (GBM) after surgery or biopsy includes concurrent chemoradiation followed by maintenance temozolomide (TMZ) with tumor treating fields (TTFields). Preclinical studies suggest TTFields and radiotherapy work synergistically. We report the results of our trial evaluating the safety of TTFields used concurrently with chemoradiation. Methods: This is a single-arm pilot study (clinicaltrials.gov Identifier: NCT03477110). Adult patients (age ≥ 18 years) with newly diagnosed glioblastoma and a Karnofsky performance score (KPS) of ≥ 60 were eligible. All patients received concurrent scalp-sparing radiation (60 Gy in 30 fractions) with TMZ (75 mg/m2 daily) and TTFields (200 kHz). Maintenance therapy included TMZ and continuation of TTFields. Scalp-sparing radiation treatment was used to reduce radiation dermatitis. Radiation treatment was delivered through the TTFields arrays. The primary endpoint was safety and toxicity of tri-modality treatment within 30 days of completion of chemoradiation treatment. Results: There were 30 patients enrolled, including 20 (66.7%) men and 10 (33.3%) women, with a median age of 58 years (range 19 to 77 years). Median KPS was 90 (range 70 to 100). A total of 12 (40%) patients received a gross total resection and 18 (60%) patients had a subtotal resection. A total of 12 (40%) patients had multifocal disease at presentation. There were 20 (66.7%) patients who had unmethylated O(6)-methylguanine-DNA-methyltransferase (MGMT) promotor status and 10 (33.3%) patients who had methylated MGMT promoter status. Median follow-up was 15.2 months (range 1.7 to 23.6 months). Skin adverse events were noted in 83.3% of patients, however, these were limited to Grade 1 or 2 events, which resolved spontaneously or with topical medications. The primary end point was met; no TTFields discontinuation occurred during the evaluation period due to high grade scalp toxicity. A total of 27 (90%) patients had progression, with a median progression-free survival (PFS) of 9.3 months (95% confidence interval (CI): 8.5-11.6 months). The 1-year progression-free survival was 23% (95% CI: 12%-45%). The median overall survival (OS) was 15.8 months (95% CI: 12.5 months-infinity). The 1-year overall survival was 66% (95% CI: 51%-86%). Conclusions: Concurrent TTFields with scalp-sparing chemoradiation is a feasible and well-tolerated treatment option with limited toxicity. A phase 3, randomized clinical trial (EF-32, clinicaltrials.gov Identifier: NCT04471844) investigating the clinical benefit of concurrent TTFields with chemoradiation treatment is currently enrolling. Clinical Trial Registration: Clinicaltrials.gov, identifier NCT03477110.

Is Timing of Steroid Exposure Prior to Immune Checkpoint Inhibitor Initiation Associated with Treatment Outcomes in Melanoma? A Population-Based Study.

Immune checkpoint inhibitors (ICIs) harness the immune system and are the therapy of choice for multiple cancers. Although immunosuppressive agents such as steroids are also used in many cancers, it is unknown how their timing affects treatment outcomes. Thus, we investigated the relationship between the timing of steroid exposure preceding ICI administration and subsequent treatment outcomes in melanoma. This population-based study utilized the SEER-Medicare-linked database to identify patients diagnosed with melanoma between 1991 and 2015 and receiving ICIs between 2010 and 2016, examining last steroid exposure in the 12 months preceding ICI. The main outcome was all-cause mortality (ACM) after ICIs. Modifications of the Cox proportional hazards model were used to calculate time-dependent hazards. Of 1671 patients with melanoma receiving ICIs, 907 received steroids. Compared with no steroids, last steroid exposures ≤1 month and 1-3 months prior to ICIs were associated with a 126% and 51% higher ACM within 3 months post ICI initiation, respectively (hazard ratio (HR): 2.26, 95% CI: 1.65-3.08; and HR: 1.51, 95% CI: 1.01-2.27). Steroid exposure within 3 months of initiating ICIs was associated with increased mortality up to 6 months after ICI. Further investigation is warranted to elucidate mechanisms affecting outcomes due to steroids.

Corrigendum to: Impact of lymphopenia on survival for elderly patients with glioblastoma: A secondary analysis of the CCTG CE.6 (EORTC 26062-22061, TROG 08.02) randomized clinical trial.

[This corrects the article DOI: 10.1093/noajnl/vdab153.].

Systemic bevacizumab to facilitate anticoagulation in antiphospholipid syndrome and bleeding gastrointestinal angiodysplasia.

Bleeding gastrointestinal angiodysplasia may occur in patients with vasculitis and can be challenging to treat. We describe the novel use of bevacizumab therapy to treat bleeding gastrointestinal angiodysplasia and severe anemia in a patient with eosinophilic granulomatosis with angiitis complicated by antiphospholipid antibody syndrome requiring indefinite warfarin therapy. Studies confirmed multiple bleeding jejunal angiodysplasias unamenable to endoscopic intervention, and the patient required ongoing support with iron infusions and blood transfusions to maintain a minimally acceptable hemoglobin. Given the severe anemia, need for continued, indefinite antiplatelet and anticoagulation therapy, and failure of standard treatment approaches, the patient was initiated on systemic bevacizumab therapy, on the basis of prior documented success of bevacizumab to manage gastrointestinal telangiectasias in patients with hereditary hemorrhagic telangiectasia. Bevacizumab was highly effective, with rapid resolution of bleeding, normalization of hemoglobin, liberation from hematologic support and no adverse events, including no thromboembolic events. Vascular endothelial growth factor (VEGF-A) rose paradoxically after initiation of bevacizumab and normalized after its discontinuation. Given these findings, use of systemic bevacizumab to manage bleeding angiodysplasia in patients with acquired vascular disorders merits further study.

Impact of lymphopenia on survival for elderly patients with glioblastoma: A secondary analysis of the CCTG CE.6 (EORTC 26062-22061, TROG03.01) randomized clinical trial.

BACKGROUND: Lymphopenia may lead to worse outcomes for glioblastoma patients. This study is a secondary analysis of the CCTG CE.6 trial evaluating the impact of chemotherapy and radiation on lymphopenia, and effects of lymphopenia on overall survival (OS). METHODS: CCTG CE.6 randomized elderly glioblastoma patients (≥ 65 years) to short-course radiation alone (RT) or short-course radiation with temozolomide (RT + TMZ). Lymphopenia (mild-moderate: grade 1-2; severe: grade 3-4) was defined per CTCAE v3.0, and measured at baseline, 1 week and 4 weeks post-RT. Preselected key factors for analysis included age, sex, ECOG, resection extent, MGMT methylation, Mini-Mental State Examination, and steroid use. Multinomial logistic regression and multivariable Cox regression models were used to identify lymphopenia-associated factors and association with survival. RESULTS: Five hundred and sixty-two patients were analyzed (281 RT vs 281 RT+TMZ). At baseline, both arms had similar rates of mild-moderate (21.4% vs 21.4%) and severe (3.2% vs 2.9%) lymphopenia. However, at 4 weeks post-RT, RT+TMZ was more likely to develop lymphopenia (mild-moderate: 27.9% vs 18.2%; severe: 9.3% vs 1.8%; p<0.001). Developing any lymphopenia post-RT was associated with baseline lymphopenia (P < .001). Baseline lymphopenia (hazard ratio [HR] 1.3) was associated with worse OS (HR: 1.30, 95% confidence interval [CI] 1.05-1.62; P = .02), regardless of MGMT status. CONCLUSIONS: Development of post-RT lymphopenia is associated with addition of TMZ and baseline lymphopenia and not with RT alone in patients treated with short-course radiation. However, regardless of MGMT status, only baseline lymphopenia is associated with worse OS, which may be considered as a prognostic biomarker for elderly glioblastoma patients.

Systemic bevacizumab for refractory bleeding and transfusion-dependent anemia in Heyde syndrome.

Heyde syndrome, the co-occurrence of aortic stenosis and bleeding gastrointestinal (GI) angiodysplasia, is managed with aortic valve replacement. However, severe bleeding and anemia can preclude safe use of the antiplatelet or anticoagulant therapy required for this intervention. We present a case of the novel and successful treatment of severe, refractory bleeding and transfusion dependence with antiangiogenic therapy in a patient with Heyde syndrome. After systemic bevacizumab was initiated, the patient achieved durable hemostasis with normalization of hemoglobin and liberation from red cell transfusion and dependence on iron infusion; aspirin therapy was successfully initiated where it had previously failed. This durable hemostasis facilitated her subsequent successful transcatheter aortic valve replacement. Plasma vascular endothelial growth factor levels, which were monitored during therapy, paradoxically rose after bevacizumab was initiated but normalized after it was discontinued. Given the angiogenic dysregulation of Heyde syndrome, systemic bevacizumab may be an effective and safe targeted therapy for managing refractory GI bleeding, which thereby facilitates antiplatelet therapy and aortic valve replacement in these challenging cases. Additional investigation into the therapeutic role of inhibiting angiogenesis as a hemostatic modality in Heyde syndrome is warranted.