A novel computational pathology approach for identifying gene signatures prognostic of disease-free survival for papillary thyroid carcinomas.

INTRODUCTION: Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with the classical and follicular variants representing most cases. Despite generally favorable prognoses, approximately 10% of patients experience recurrence post-surgery and radioactive iodine therapy. Attempts to stratify risk of recurrence have relied on gene expression-based prognostic and predictive signatures with a focus on mutations of well-known driver genes, while hallmarks of tumor morphology have been ignored. OBJECTIVES: We introduce a new computational pathology approach to develop prognostic gene signatures for PTC that is informed by quantitative features of tumor and immune cell morphology. METHODS: We quantified nuclear and immune-related features of tumor morphology to develop a pathomic signature, which was then used to inform an RNA-expression signature model provides a notable advancement in risk stratification compared to both standalone and pathology-informed gene-expression signatures. RESULTS: There was a 17.8% improvement in the C-index (from 0.605 to 0.783) for 123 cPTCs and 15% (from 0.576 to 0.726) for 38 fvPTCs compared to the standalone gene-expression signature. Hazard ratios also improved for cPTCs from 0.89 (0.67,0.99) to 4.43 (3.65,6.68) and fvPTC from 0.98 (0.76,1.32) to 2.28 (1.87,3.64). We validated the image-based risk model on an independent cohort of 32 cPTCs with hazard ratio 1.8 (1.534,2.167).

Haplo-cord transplant. Realizing the potential of umbilical cord blood grafts. - A review of techniques and analysis of outcomes.

The combination of cord blood transplant with progenitor cells from partially HLA-matched adult donors (haplo-cord transplant) has been used over the past two decades. In Europe and the US the adult donor graft is CD34 selected and provides early hematopoiesis, but durable engraftment derives from the cord blood graft (CD34 selected haplo-cord). Neutrophil recovery is prompt and rates of acute and chronic GVHD are low. Recent Chinese studies combine cord blood grafts with T-replete haplo-identical grafts (unmodified haplo-cord). The haplo graft usually establishes dominance and UCB chimerism is rarely detected. Comparison studies suggest considerably decreased rates of relapse and improved outcomes, compared with either haplo-identical transplant or CBU transplant, particularly in patients with advanced leukemia. A recent prospective randomized study confirms this. Haplo-cord mitigates the engraftment delay of UCB transplant. The unique biology of UCB grafts results in low GVHD and improved GVL especially beneficial in high-risk disease.

A Pilot Trial of Proton-Based Cardiac Sparing Accelerated Fractionated Radiation Therapy in Unresectable Non-small Cell Lung Cancer With Extended Durvalumab Therapy (PARTICLE-D).

PURPOSE: Concurrent chemoradiation therapy is the current nonsurgical standard of care for locally advanced non-small cell lung cancer. However, this is a difficult regimen to tolerate, especially for those who are elderly, have multiple comorbidities, or have poor performance status. Alternative treatment regimens are needed for this vulnerable population. We report initial results of concurrent durvalumab, an immune checkpoint inhibitor, and hypofractionated, dose-escalating, proton external beam radiation therapy (EBRT). METHODS AND MATERIALS: This phase 1, pilot dose escalation trial enrolled 7 patients with newly diagnosed stage IIIA to IIIC non-small cell lung cancer and who were unable or unwilling to undergo concurrent chemoradiation therapy. Patients previously treated with immunotherapy were excluded. Five patients in this 3 + 3 study design received a fixed dose of durvalumab on day 1 of each 28-day cycle plus hypofractionated proton EBRT with initial dose of 60 Gy (Arm 1) in 20 fractions while 2 patients received the escalation dose of 69 Gy in 23 fractions (Arm 2). The primary objective was to assess safety and the secondary objective was to assess feasibility and adverse events. RESULTS: All patients experienced treatment-related adverse events, primarily grades 1 and 2. Pneumonitis and anemia were the most common. Only 1 dose-limiting toxicity occurred in arm 1, which was a grade 3 pneumonitis leading to grade 5 pneumonia. Additionally, 2 delayed-onset grade 5 tracheal necrosis events occurred >13 months after treatment initiation. CONCLUSIONS: Concurrent durvalumab plus hypofractionated proton EBRT was well tolerated in the short term. However, 3 treatment-related deaths, including 2 delayed-onset grade 5 tracheal necroses negatively impacted overall safety. A dose de-escalation protocol of proton-based radiation therapy plus durvalumab is warranted.

A prognostic and predictive computational pathology immune signature for ductal carcinoma in situ: retrospective results from a cohort within the UK/ANZ DCIS trial.

BACKGROUND: The density of tumour-infiltrating lymphocytes (TILs) could be prognostic in ductal carcinoma in situ (DCIS). However, manual TIL quantification is time-consuming and suffers from interobserver and intraobserver variability. In this study, we developed a TIL-based computational pathology biomarker and evaluated its association with the risk of recurrence and benefit of adjuvant treatment in a clinical trial cohort. METHODS: In this retrospective cohort study, a computational pathology pipeline was developed to generate a TIL-based biomarker (CPath TIL categories). Subsequently, the signature underwent a masked independent validation on H&E-stained whole-section images of 755 patients with DCIS from the UK/ANZ DCIS randomised controlled trial. Specifically, continuous biomarker CPath TIL score was calculated as the average TIL density in the DCIS microenvironment and dichotomised into binary biomarker CPath TIL categories (CPath TIL-high vs CPath TIL-low) using the median value as a cutoff. The primary outcome was ipsilateral breast event (IBE; either recurrence of DCIS [DCIS-IBE] or invasive progression [I-IBE]). The Cox proportional hazards model was used to estimate the hazard ratio (HR). FINDINGS: CPath TIL-score was evaluable in 718 (95%) of 755 patients (151 IBEs). Patients with CPath TIL-high DCIS had a greater risk of IBE than those with CPath TIL-low DCIS (HR 2·10 [95% CI 1·39-3·18]; p=0·0004). The risk of I-IBE was greater in patients with CPath TIL-high DCIS than those with CPath TIL-low DCIS (3·09 [1·56-6·14]; p=0·0013), and the risk of DCIS-IBE was non-significantly higher in those with CPath TIL-high DCIS (1·61 [0·95-2·72]; p=0·077). A significant interaction (pinteraction=0·025) between CPath TIL categories and radiotherapy was observed with a greater magnitude of radiotherapy benefit in preventing IBE in CPath TIL-high DCIS (0·32 [0·19-0·54]) than CPath TIL-low DCIS (0·40 [0·20-0·81]). INTERPRETATION: High TIL density is associated with higher recurrence risk-particularly of invasive recurrence-and greater radiotherapy benefit in patients with DCIS. Our TIL-based computational pathology signature has a prognostic and predictive role in DCIS. FUNDING: National Cancer Institute under award number U01CA269181, Cancer Research UK (C569/A12061; C569/A16891), and the Breast Cancer Research Foundation, New York (NY, USA).

Image analysis Uncovers associations between immune landscape, collagen structure, and neoadjuvant chemotherapy in high-grade serous ovarian carcinomas.

Background: The changes in the tumor microenvironment of high-grade serous ovarian carcinomas following neoadjuvant chemotherapy are a complex area of study. Previous research underscores the importance of investigating the immune and collagen components within the tumor microenvironment for prognostic implications. Methods: In this study, we utilized computational pathology techniques with Hematoxylin and Eosin-stained images to quantitatively characterize the immune and collagen architecture within the tumor microenvironment of patients with high-grade serous ovarian carcinoma. Results: Our analysis of 12 pre- and post-neoadjuvant chemotherapy images revealed an increase in immune infiltrate, primarily within the epithelial region. Additionally, post-neoadjuvant chemotherapy images exhibited chaotic collagen architecture compared to pre-neoadjuvant chemotherapy images. Importantly, features extracted from post-neoadjuvant chemotherapy images showed associations with overall survival, potentially aiding in the selection of patients for immunotherapy trials. Conclusions: These findings offer critical insights into the changes in the tumor microenvironment of high-grade serous ovarian carcinomas following neoadjuvant chemotherapy and their potential implications for clinical outcomes.

Outcomes of initial therapy for synchronous brain metastases from small cell lung cancer: a single-institution retrospective analysis.

Small cell lung cancer (SCLC) has a propensity for brain metastases, which is associated with poor prognosis. We sought to determine predictors of overall survival (OS) and brain progression-free survival (bPFS) in SCLC patients with synchronous brain metastases at the time of initial SCLC diagnosis. A total of 107 SCLC patients with synchronous brain metastases treated at a single institution were included in this retrospective analysis. These patients had brain lesions present on initial staging imaging. Survival was estimated using the Kaplan-Meier method with log-rank test. Factors predictive of OS and bPFS were analyzed using Cox proportional hazards regression model. Median OS for the entire cohort was 9 months (interquartile range, 4.2-13.8 months) and median bPFS was 7.3 months (interquartile range, 3.5-11.1 months). OS was 30.3% at 1 year and 14.4% at 2 years, while bPFS was 22.0% at 1 year and 6.9% at 2 years. The median number of brain lesions at diagnosis was 3 (interquartile range, 2-8), and the median size of the largest metastasis was 2.0 cm (interquartile range, 1.0-3.3 cm). Increased number of brain lesions was significantly associated with decreased OS. Patients who received both chemotherapy and whole brain radiation therapy (WBRT) had improved OS (P=0.02) and bPFS (P=0.005) compared to those who had either chemotherapy or WBRT alone. There was no significant difference in OS or bPFS depending on the sequence of therapy or the dose of WBRT. Thirteen patients underwent upfront brain metastasis resection, which was associated with improved OS (P=0.02) but not bPFS (P=0.09) compared to those who did not have surgery. The combination of chemotherapy and WBRT was associated with improved OS and bPFS compared to either modality alone. Upfront brain metastasis resection was associated with improved OS but not bPFS compared to those who did not have surgery.

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics.

Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., multiple-vessel disease, spread of the disease along the vessel, stable calcifications, numbers of lesions, and density). We used novel, hand-crafted calcification features (calcium-omics); Cox time-to-event modeling; elastic net; and up and down synthetic sampling methods for imbalanced data, to assess MACE risk. We used 2457 CT calcium score (CTCS) images enriched for MACE events from our large no-cost CLARIFY program (ClinicalTrials.gov Identifier: NCT04075162). Among calcium-omics features, numbers of calcifications, LAD mass, and diffusivity (a measure of spatial distribution) were especially important determinants of increased risk, with dense calcification (> 1000HU, stable calcifications) associated with reduced risk Our calcium-omics model with (training/testing, 80/20) gave C-index (80.5%/71.6%) and 2-year AUC (82.4%/74.8%). Although the C-index is notoriously impervious to model improvements, calcium-omics compared favorably to Agatston and gave a significant difference (P < 0.001). The calcium-omics model identified 73.5% of MACE cases in the high-risk group, a 13.2% improvement as compared to Agatston, suggesting that calcium-omics could be used to better identity candidates for intensive follow-up and therapies. The categorical net-reclassification index was NRI = 0.153. Our findings from this exploratory study suggest the utility of calcium-omics in improved risk prediction. These promising results will pave the way for more extensive, multi-institutional studies of calcium-omics.

Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.

Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this study we employed machine learning and statistical atlas-based approaches to explore possible changes in lung shape among COVID-19 patients and evaluated whether the extent of these changes was associated with COVID-19 severity. On a large multi-institutional dataset (N = 3443), three different populations were defined; a) healthy (no COVID-19), b) mild COVID-19 (no ventilator required), c) severe COVID-19 (ventilator required), and the presence of lung shape differences between them were explored using baseline chest CT. Significant lung shape differences were observed along mediastinal surfaces of the lungs across all severity of COVID-19 disease. Additionally, differences were seen on basal surfaces of the lung when compared between healthy and severe COVID-19 patients. Finally, an AI model (a 3D residual convolutional network) characterizing these shape differences coupled with lung infiltrates (ground-glass opacities and consolidation regions) was found to be associated with COVID-19 severity.

Computational Pathology Assessments of Cardiac Stromal Remodeling: Clinical Correlates and Prognostic Implications in Heart Transplantation.

Both overt and indolent inflammatory insults in heart transplantation can accelerate pathologic cardiac remodeling, but there are few tools for monitoring the speed and severity of remodeling over time. To address this need, we developed an automated computational pathology system to measure pathologic remodeling in transplant biopsy samples in a large, retrospective cohort of n=2167 digitized heart transplant biopsy slides. Biopsy images were analyzed to identify the pathologic stromal changes associated with future allograft loss or advanced allograft vasculopathy. Biopsy images were then analyzed to assess which historical allo-inflammatory events drive progression of these pathologic stromal changes over time in serial biopsy samples. The top-5 features of pathologic stromal remodeling most strongly associated with adverse outcomes were also strongly associated with histories of both overt and indolent inflammatory events. Our findings identify previously unappreciated subgroups of higher- and lower-risk transplant patients, and highlight the translational potential of digital pathology analysis.

Interpretable deep learning insights: Unveiling the role of 1 Gy volume on lymphopenia after radiotherapy in breast cancer.

BACKGROUND: Lymphopenia is known for its significance on poor survivals in breast cancer patients. Considering full dosimetric data, this study aimed to develop and validate predictive models for lymphopenia after radiotherapy (RT) in breast cancer. MATERIAL AND METHODS: Patients with breast cancer treated with adjuvant RT were eligible in this multicenter study. The study endpoint was lympopenia, defined as the reduction in absolute lymphocytes and graded lymphopenia after RT. The dose-volume histogram (DVH) data of related critical structures and clinical factors were taken into account for the development of dense neural network (DNN) predictive models. The developed DNN models were validated using external patient cohorts. RESULTS: A total of 918 consecutive patients with invasive breast cancer enrolled. The training, testing, and external validating datasets consisted of 589, 203, and 126 patients, respectively. Treatment volumes at nearly all dose levels of the DVH were significant predictors for lymphopenia following RT, including volumes at very low-dose 1 Gy (V1) of organs at risk (OARs) including lung, heart and body, especially ipsilateral-lung V1. A final DNN model, combining full DVH dosimetric parameters of OARs and three key clinical factors, achieved a predictive accuracy of 75 % or higher. CONCLUSION: This study demonstrated and externally validated the significance of full dosimetric data, particularly the volume of low dose at as low as 1 Gy of critical structures on lymphopenia after radiation in patients with breast cancer. The significance of V1 deserves special attention, as modern VMAT RT technology often has a relatively high value of this parameter. Further study is warranted for RT plan optimization.

Patients on Antithrombotic Agents with Small Bowel Bleeding -Yield of Small Bowel Capsule Endoscopy and Subsequent Management.

BACKGROUND AND AIMS: Small bowel gastrointestinal bleeding (GIB) is associated with multiple blood transfusions, prolonged and/or multiple hospital admissions, utilization of significant healthcare resources, and negative effects on patient quality of life. There is a well-recognized association between antithrombotic medications and small bowel GIB. We aimed to identify the diagnostic yield of small bowel capsule endoscopy (SBCE) in patients on antithrombotic medications and the impact of SBCE on treatment course. METHODS: The electronic medical records of nineteen hundred eighty-six patients undergoing SBCE were retrospectively reviewed. RESULTS: The diagnostic yield for detecting stigmata of recent bleeding and/or actively bleeding lesions in SBCE was higher in patients that were on antiplatelet agents (21.6%), patients on anticoagulation (22.5%), and in patients that had their SBCE performed while they were inpatient (21.8%), when compared to the patients not on antiplatelet agents (12.1%), patients not on anticoagulation (13.5%), and with patients that had their SBCE performed in the outpatient setting (12%). Of 318 patients who had stigmata of recent bleeding and/or actively bleeding lesion(s) identified on SBCE, SBCE findings prompted endoscopic evaluation (small bowel enteroscopy, esophagogastroduodenoscopy (EGD), and/or colonoscopy) in 25.2%, with endoscopic hemostasis attempted in 52.5%. CONCLUSIONS: Our study, the largest conducted to date, emphasizes the importance of performing SBCE as part of the evaluation for suspected small bowel bleeding, particularly in patients taking antithrombotic therapy, and especially during their inpatient hospital stay.

Neoadjuvant Dual Checkpoint Inhibitors vs Anti-PD1 Therapy in High-Risk Resectable Melanoma: A Pooled Analysis.

Importance: Despite the clear potential benefits of neoadjuvant therapy, the optimal neoadjuvant regimen for patients with high-risk resectable melanoma (HRRM) is not known. Objective: To compare the safety and efficacy of dual checkpoint inhibitors with anti-programmed cell death protein-1 (anti-PD1) therapy in a neoadjuvant setting among patients with HRRM. Design, Setting, and Participants: In this pooled analysis of clinical trials, studies were selected provided they investigated immune checkpoint inhibitor treatment, were published between January 2018 and March 2023, and were phase 1, 2, or 3 clinical trials. Participant data included in the analysis were derived from trials evaluating the efficacy and safety of anti-PD1 monotherapy and the combination of anti-cytotoxic T lymphocyte-associated protein-4 with anti-PD1 in the neoadjuvant setting, specifically among patients with HRRM. Interventions: Patients were treated with either anti-PD1 monotherapy; dual checkpoint inhibition (DCPI) with a conventional dose of 3-mg/kg ipilimumab and 1-mg/kg nivolumab; or DCPI with an alternative-dose regimen of 1-mg/kg ipilimumab and 3-mg/kg nivolumab. Main Outcomes and Measures: The main outcomes were radiologic complete response (rCR), radiologic overall objective response (rOOR), and radiologic progressive disease. Also, pathologic complete response (pCR), the proportion of patients undergoing surgical resection, and occurrence of grade 3 or 4 immune-related adverse events (irAEs) were considered. Results: Among 573 patients enrolled in 6 clinical trials, neoadjuvant therapy with DCPI was associated with higher odds of achieving pCR compared with anti-PD1 monotherapy (odds ratio [OR], 3.16; P < .001). DCPI was associated with higher odds of grade 3 or 4 irAEs compared with anti-PD1 monotherapy (OR, 3.75; P < .001). When comparing the alternative-dose ipilimumab and nivolumab (IPI-NIVO) regimen with conventional-dose IPI-NIVO, no statistically significant difference in rCR, rOOR, radiologic progressive disease, or pCR was noted. However, the conventional-dose IPI-NIVO regimen was associated with increased grade 3 or 4 irAEs (OR, 4.76; P < .001). Conventional-dose IPI-NIVO was associated with greater odds of achieving improved rOOR (OR, 1.95; P = .046) and pCR (OR, 2.99; P < .001) compared with anti-PD1 monotherapy. The alternative dose of IPI-NIVO also was associated with higher odds of achieving rCR (OR, 2.55; P = .03) and pCR (OR, 3.87; P < .001) compared with anti-PD1 monotherapy. The risk for grade 3 or 4 irAEs is higher with both the conventional-dose (OR, 9.59; P < .001) and alternative-dose IPI-NIVO regimens (OR, 2.02; P = .02) compared with anti-PD1 monotherapy. Conclusion and Relevance: In this pooled analysis of 6 clinical trials, although DCPI was associated with increased likelihood of achieving pathological and radiologic responses, the associated risk for grade 3 or 4 irAEs was significantly lower with anti-PD1 monotherapy in the neoadjuvant setting for HRRM. Additionally, compared with alternative-dose IPI-NIVO, the conventional dose of IPI-NIVO was associated with increased risk for grade 3 or 4 irAEs, with no significant distinctions in radiologic or pathologic efficacy.

Failing to Make the Grade: Conventional Cardiac Allograft Rejection Grading Criteria Are Inadequate for Predicting Rejection Severity.

BACKGROUND: Cardiac allograft rejection is the leading cause of early graft failure and is a major focus of postheart transplant patient care. While histological grading of endomyocardial biopsy samples remains the diagnostic standard for acute rejection, this standard has limited diagnostic accuracy. Discordance between biopsy rejection grade and patient clinical trajectory frequently leads to both overtreatment of indolent processes and delayed treatment of aggressive ones, spurring the need to investigate the adequacy of the current histological criteria for assessing clinically important rejection outcomes. METHODS: N=2900 endomyocardial biopsy images were assigned a rejection grade label (high versus low grade) and a clinical trajectory label (evident versus silent rejection). Using an image analysis approach, n=370 quantitative morphology features describing the lymphocytes and stroma were extracted from each slide. Two models were constructed to compare the subset of features associated with rejection grades versus those associated with clinical trajectories. A proof-of-principle machine learning pipeline-the cardiac allograft rejection evaluator-was then developed to test the feasibility of identifying the clinical severity of a rejection event. RESULTS: The histopathologic findings associated with conventional rejection grades differ substantially from those associated with clinically evident allograft injury. Quantitative assessment of a small set of well-defined morphological features can be leveraged to more accurately reflect the severity of rejection compared with that achieved by the International Society of Heart and Lung Transplantation grades. CONCLUSIONS: Conventional endomyocardial samples contain morphological information that enables accurate identification of clinically evident rejection events, and this information is incompletely captured by the current, guideline-endorsed, rejection grading criteria.

A multicenter study of posttransplantation low-dose inotuzumab ozogamicin to prevent relapse of acute lymphoblastic leukemia.

ABSTRACT: The curative potential of allogeneic hematopoietic transplantation (allo-HCT) in patients with acute lymphoblastic leukemia (ALL) is hampered by relapse. Inotuzumab ozogamicin (INO) is an anti-CD22 monoclonal antibody bound to calicheamicin, which has significant activity against ALL. We hypothesized that low-dose INO would be safe and feasible after allo-HCT. Therefore, we conducted a phase 1 study to determine the dose and safety in this setting. Patients were eligible if they were aged 16 to 75 years, had undergone allo-HCT for CD22+ ALL, were in complete remission (CR) after allo-HCT, had high risk of recurrence, were between day 40 and 100 after allo-HCT with adequate graft function, and did not have a history of sinusoidal obstruction syndrome (SOS). The objectives of this trial were to define INO maximum tolerated dose (MTD), to determine post-allo-HCT INO safety, and to measure 1-year progression-free survival (PFS). The trial design followed a "3+3" model. The treatment consisted of INO given on day 1 of 28-day cycles. Dose levels were 0.3 mg/m2, 0.4 mg/m2, 0.5 mg/m2, and 0.6 mg/m2. Median age was 44 years (range, 17-66 years; n = 18). Disease status at transplantation was first CR (n = 14) or second CR or beyond (n = 4). Preparative regimen was of reduced intensity in 72% of patients who received transplantation. Most common toxicity was thrombocytopenia. There were no instances of SOS; the MTD was 0.6 mg/m2. One-year nonrelapse mortality was 5.6%. With a median follow-up of 18.1 months (range, 8.6-59 months) 1-year post-allo-HCT PFS and overall survival is 89% and 94%, respectively. Low-dose INO has a favorable safety profile and was associated with high rates of 1-year PFS. This trial was registered at www.clinicaltrials.gov as #NCT03104491.

Impact of Visceral Obesity on Clinical Outcome and Quality of Life for Patients with Multiple Myeloma: A Secondary Data Analysis of STaMINA (BMT CTN 0702) Trial.

Obesity is a common health problem in patients with multiple myeloma (MM) that has been linked to poor clinical outcomes and quality of life (QoL). We conducted a secondary analysis of the BMT CTN 0702, a randomized, controlled trial comparing outcomes of 3 treatment interventions after a single hematopoietic cell transplantation (HCT) (n = 758), to investigate the impact of visceral obesity, as measured by waist-to-hip ratio (WHR), on clinical outcomes and QoL in MM patients. A total of 549 MM patients, median age 55.5 years, were enrolled in the study. The majority of patients received triple-drug antimyeloma initial therapy before enrollment, and 29% had high-risk disease according to cytogenetic assessment. The median duration of follow-up was 6 years. There was no significant association between WHR and progression-free survival (PFS) or overall survival (OS) in MM patients undergoing HCT. Similarly, body mass index (BMI) did not significantly predict PFS or OS. Furthermore, there was no significant correlation between WHR and QoL measures. This study suggests that visceral obesity, as measured by WHR, might not have a significant impact on clinical outcomes in MM patients undergoing HCT. These findings add to the existing literature on the topic and provide valuable information for healthcare professionals and MM patients. Further studies are needed to confirm these results and to investigate other potential factors that may affect clinical outcomes and QoL in this patient population using modern imaging technologies to assess visceral obesity.

Computational pathology identifies immune-mediated collagen disruption to predict clinical outcomes in gynecologic malignancies.

BACKGROUND: The role of immune cells in collagen degradation within the tumor microenvironment (TME) is unclear. Immune cells, particularly tumor-infiltrating lymphocytes (TILs), are known to alter the extracellular matrix, affecting cancer progression and patient survival. However, the quantitative evaluation of the immune modulatory impact on collagen architecture within the TME remains limited. METHODS: We introduce CollaTIL, a computational pathology method that quantitatively characterizes the immune-collagen relationship within the TME of gynecologic cancers, including high-grade serous ovarian (HGSOC), cervical squamous cell carcinoma (CSCC), and endometrial carcinomas. CollaTIL aims to investigate immune modulatory impact on collagen architecture within the TME, aiming to uncover the interplay between the immune system and tumor progression. RESULTS: We observe that an increased immune infiltrate is associated with chaotic collagen architecture and higher entropy, while immune sparse TME exhibits ordered collagen and lower entropy. Importantly, CollaTIL-associated features that stratify disease risk are linked with gene signatures corresponding to TCA-Cycle in CSCC, and amino acid metabolism, and macrophages in HGSOC. CONCLUSIONS: CollaTIL uncovers a relationship between immune infiltration and collagen structure in the TME of gynecologic cancers. Integrating CollaTIL with genomic analysis offers promising opportunities for future therapeutic strategies and enhanced prognostic assessments in gynecologic oncology.

The role of cells that are part of our immune system in altering the structure of the protein collagen within cancers is not fully understood, particularly within cancers that affect women such as ovarian, cervical and uterine cancers. Here, we developed a computer-based method called CollaTIL to explore how immune cells influence collagen in these tumors and affect their growth. We found that a higher presence of immune cells leads to less organized collagen in the tumor. Conversely, when there are fewer immune cells, the collagen tends to be more structured. Additionally, CollaTIL identifies patterns that predict patient outcomes in these cancers. These findings not only enhance our understanding of tumor biology but also may be useful in helping clinicians to predict which patients are at risk of their disease progressing.

Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study.

BACKGROUND: Radiomics is a method within medical image analysis that involves the extraction of quantitative data from radiologic scans, often in conjunction with machine learning algorithms to phenotype disease appearance, prognosticate disease outcome, and predict treatment response. However, variance in CT scanner acquisition parameters, such as convolution kernels or pixel spacing, can impact radiomics texture feature values. PURPOSE: The extent to which the parameters influence radiomics features continues to be an active area of investigation. In this study, we describe a novel approach, Acquisition Impact on Radiomics Estimation (AcquIRE), to rank the impact of CT acquisition parameters on radiomic texture features. METHODS: In this work, we used three chest CT imaging datasets (n = 749 patients) from nine sites comprising: i) lung granulomas and adenocarcinomas (D1) (10 and 52 patients, respectively); ii) minimal and frank invasive adenocarcinoma (D2) (74 and 145 patients); and iii) early-stage NSCLC patients (D3) (315 patients). Datasets D2 and D3 were collected from four sites each, and D1 from a single site. For each patient, 744 texture features and nine acquisition parameters were extracted and utilized to evaluate which parameters impact radiomic features the most. The AcquIRE method establishes a relative assessment between acquisition parameters and radiomic texture featuresa through the creation of a classification model, which is then utilized to assess the rank of the acquisition parameters. RESULTS: Across the use cases, CT software version and convolution kernel parameters were found to have the most variance. In D1, it was observed that the Haralick texture feature family was the least affected by variations in acquisition parameters, while the Gabor feature family was the most impacted. However, in datasets D2 and D3, the Gabor features were found to be the least affected. Our findings suggest that the impact on radiomic parameters is as much a function of the problem in question as it is acquisition parameters. CONCLUSIONS: The software version and convolution kernel parameters impacted the radiomics feature the most.

Phase II Clinical Trial of Pembrolizumab and Chemotherapy Reveals Distinct Transcriptomic Profiles by Radiologic Response in Metastatic Triple-Negative Breast Cancer.

PURPOSE: A single arm, phase II trial of carboplatin, nab-paclitaxel, and pembrolizumab (CNP) in metastatic triple-negative breast cancer (mTNBC) was designed to evaluate overall response rate (ORR), progression-free survival (PFS), duration of response (DOR), safety/tolerability, overall survival (OS), and identify pathologic and transcriptomic correlates of response to therapy. PATIENTS AND METHODS: Patients with ≤2 prior therapies for metastatic disease were treated with CNP regardless of tumor programmed cell death-ligand 1 status. Core tissue biopsies were obtained prior to treatment initiation. ORR was assessed using a binomial distribution. Survival was analyzed via the Kaplan-Meier method. Bulk RNA sequencing was employed for correlative studies. RESULTS: Thirty patients were enrolled. The ORR was 48.0%: 2 (7%) complete responses (CR), 11 (41%) partial responses (PR), and 8 (30%) stable disease (SD). The median DOR for patients with CR or PR was 6.4 months [95% confidence interval (CI), 4-8.5 months]. For patients with CR, DOR was >24 months. Overall median PFS and OS were 5.8 (95% CI, 4.7-8.5 months) and 13.4 months (8.9-17.3 months), respectively. We identified unique transcriptomic landscapes associated with each RECIST category of radiographic treatment response. In CR and durable PR, IGHG1 expression was enriched. IGHG1high tumors were associated with improved OS (P = 0.045) and were concurrently enriched with B cells and follicular helper T cells, indicating IGHG1 as a promising marker for lymphocytic infiltration and robust response to chemo-immunotherapy. CONCLUSIONS: Pretreatment tissue sampling in mTNBC treated with CNP reveals transcriptomic signatures that may predict radiographic responses to chemo-immunotherapy.

Dosimetric Effect of Thymus and Thoracic Duct on Radiation-Induced Lymphopenia in Patients With Primary Lung Cancer Who Received Thoracic Radiation.

Purpose: Radiation-induced lymphopenia is a well-recognized factor for tumor control and survival in patients with cancer. This study aimed to determine the role of radiation dose to the thymus and thoracic duct on radiation-induced lymphopenia. Methods and Materials: Patients with primary lung cancer treated with thoracic radiation therapy between May 2015 and February 2020 with whole blood count data were eligible. Clinical characteristics, including age, gender, histology, stage, chemotherapy regimen, radiation dosimetry, and absolute lymphocyte count (ALC) were collected. The thymus and thoracic duct were contoured by one investigator for consistency and checked by one senior physician. The primary endpoint was radiation-induced decrease in lymphocytes, defined as the difference in ALC (DALC) before and after radiation therapy. Results: The data of a total of 116 consecutive patients were retrospectively retrieved. Significant correlations were found between DALC and several clinical factors. These factors include stage, chemotherapy or concurrent chemoradiation, biologically effective dose (BED), mean lung dose, mean body dose, effective dose to immune cells (EDIC), mean thymus dose (MTD), and mean thoracic duct dose (MTDD) (all P < .05). Ridge regression showed that DALC = 0.0063 × BED + 0.0172 × EDIC + 0.0002 × MTD + 0.0147 × MTDD + 0.2510 (overall P = .00025 and F = 5.85). The combination model has the highest area under the curve of 0.77 (P < .001) when fitting the logistic regression model on DALC categorized as binary endpoint. The sensitivity and specificity of the combined model were 89% and 58%, respectively. Conclusions: This study demonstrated for the first time that radiation doses to the thymus and thoracic duct are strongly associated with radiation-induced lymphopenia patients with lung cancer. Further validation studies are needed to implement thymus and thoracic duct as organs at risk.

The Impact of Prophylactic Cranial Irradiation and Consolidative Thoracic Radiation Therapy for Extensive Stage Small-Cell Lung Cancer in the Transition to the Chemo-Immunotherapy Era: A Single Institution Series.

INTRODUCTION: Extensive-stage small-cell lung cancer (ES-SCLC) continues to have poor survival due to its aggressive behavior, despite improvements with incorporation of immunotherapy with standard chemotherapy. Controversy exists regarding the role of consolidative thoracic radiation therapy (TRT) and prophylactic cranial irradiation (PCI) in ES-SCLC due to high recurrence rates. We report our institutional result of the benefit of PCI and TRT in ES-SCLC. METHODS: Patients with ES-SCLC without intracranial metastasis at diagnosis (N = 163) were included. All patients completed systemic therapy with or without immunotherapy based on time of standard of care. Cohorts were divided by systemic therapy use and further subdivided by treatment with PCI and TRT. Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method with log-rank test for comparison. The effects of TRT and PCI were estimated by multivariable (MVA) Cox regression. RESULTS: Seventy-four patients (45.4%) received TRT, and 33.1% (n = 54) received PCI. The median follow-up was 11 months (3-85 months). PCI improved median OS to 15 months from 10 months, P = .02) and median PFS to 8.5 months from 5 months (P = .02) which remained significant on MVA, P = .02 and P = .02, respectively. TRT improved OS on UVA (P = 0.002) but was not significant on MVA. TRT did not improve PFS. CONCLUSION: This study including chemotherapy and chemo-immunotherapy suggests improved outcomes with addition of PCI in patients with ES-SCLC while TRT did not show benefit to either OS or PFS. A future trial is needed to evaluate the role of TRT and PCI in the era of chemo-immunotherapy.