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Abstract Background Breast and prostate tumors are known to be less responsive to immune checkpoint inhibitors (ICIs). Tissue-based tumor mutation burden (tTMB) has emerged as a predictive biomarker of response to ICIs, including in these “cold tumors”. In clinical practice, when tTMB is not available, blood-based TMB score (bTMB) can be used to consider treatment with ICIs. Methods This retrospective, real-world study included a final cohort of metastatic breast and prostate cancer patients treated with an ICI following a liquid biopsy test. Multiple bTMB-High cut-offs were assessed. Clinical, genomic, and outcomes data were collected. We hypothesized that a cut-off of bTMB ≥10 mut/Mb is not a strong predictor of response to ICIs in this setting. The Guardant Health genomic database (GHGD) was then queried (N = 13,992) for associations of bTMB with genomic alterations. Results In the clinical cohort (N = 48), ICI treatment is offered after a median of 3 (1–9) lines of treatment. The median bTMB is 16.4 (10–186) mut/Mb. The median time on ICI and PFS is 2.1 (0–1.7) and 3.1 months (95%CI, 1.6–4.6) respectively; no difference by MSI/MMR status (p = 0.152). Response rate among eligible patients (n = 36) is 16.7%; only N = 1/6 in bTMB

Abstract 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

Background: The hostile immune environment created by allotransplantation can accelerate pathologic tissue remodeling. Both overt and indolent inflammatory insults propel this remodeling, but there is a paucity of tools for monitoring the speed and severity of remodeling over time. Methods: This retrospective cohort consisted of n = 2,167 digitized heart transplant biopsy slides along with records of prior inflammatory events and future allograft outcomes (cardiac death or allograft vasculopathy). Utilizing computational pathology analysis, biopsy images were analyzed to identify the pathologic stromal changes associated with future allograft loss or vasculopathy. Biopsy images were then analyzed to assess which historical inflammatory events drive progression of these pathologic stromal changes. Results: The top 5 features of pathologic stromal remodeling most associated with adverse allograft outcomes were also strongly associated with histories of both overt and indolent inflammatory events. Compared to controls, a history of high-grade or treated rejection was significantly associated with progressive pathologic remodeling and future adverse outcomes (32.9% vs 5.1%, p

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.

Abstract 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.

Abstract Background Patients with certain autoimmune conditions are at a reduced risk of developing breast cancer compared to the general population. Despite this, little is known about outcomes in patients with breast cancer who have a concurrent autoimmune diagnosis. Methods This study compared differences in outcomes between women with breast cancer who had or did not have an autoimmune diagnosis. The SEER‐Medicare databases (2007–2014) were used to identify patients with breast cancer and diagnosis codes were used to identify those with an autoimmune disorder. Results The studied autoimmune diseases had a prevalence of 27% among the 137,324 patients with breast cancer. Autoimmune disease was associated with significantly longer overall survival (OS) and significantly lower cancer‐specific mortality (CSM) among stage IV breast cancer patients (p

Abstract The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL’s advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867).

Abstract Chemoradiation is a common therapeutic regimen for human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). However, not all patients benefit from chemotherapy, especially patients with low-risk characteristics. We aim to develop and validate a prognostic and predictive radiomic image signature (pRiS) to inform survival and chemotherapy benefit using computed tomography (CT) scans from 491 stage I and II HPV-associated OPSCC, which were divided into three cohorts D1–D3. The prognostic performance of pRiS was evaluated on two test sets (D2, n = 162; D3, n = 269) using concordance index. Patients from D2 and D3 who received either radiotherapy alone or chemoradiation were used to validate pRiS as predictive of added benefit of chemotherapy. Seven features were selected to construct pRiS, which was found to be prognostic of overall survival (OS) on univariate analysis in D2 (hazard ratio [HR] = 2.14, 95% confidence interval [CI], 1.1–4.16, p = 0.02) and D3 (HR = 2.74, 95% CI, 1.34–5.62, p = 0.006). Chemotherapy was associated with improved OS for high-pRiS patients in D2 (radiation vs chemoradiation, HR = 4.47, 95% CI, 1.73–11.6, p = 0.002) and D3 (radiation vs chemoradiation, HR = 2.99, 95% CI, 1.04–8.63, p = 0.04). In contrast, chemotherapy did not improve OS for low-pRiS patients, which indicates these patients did not derive additional benefit from chemotherapy and could be considered for treatment de-escalation. The proposed radiomic signature was prognostic of patient survival and informed benefit from chemotherapy for stage I and II HPV-associated OPSCC patients.

Abstract Prognostic markers currently utilized in clinical practice for estrogen receptor-positive (ER+) and lymph node-negative (LN−) invasive breast cancer (IBC) patients include the Nottingham grading system and Oncotype Dx (ODx). However, these biomarkers are not always optimal and remain subject to inter-/intra-observer variability and high cost. In this study, we evaluated the association between computationally derived image features from H&E images and disease-free survival (DFS) in ER+ and LN− IBC. H&E images from a total of n = 321 patients with ER+ and LN− IBC from three cohorts were employed for this study (Training set: D1 (n = 116), Validation sets: D2 (n = 121) and D3 (n = 84)). A total of 343 features relating to nuclear morphology, mitotic activity, and tubule formation were computationally extracted from each slide image. A Cox regression model (IbRiS) was trained to identify significant predictors of DFS and predict a high/low-risk category using D1 and was validated on independent testing sets D2 and D3 as well as within each ODx risk category. IbRiS was significantly prognostic of DFS with a hazard ratio (HR) of 2.33 (95% confidence interval (95% CI) = 1.02–5.32, p = 0.045) on D2 and a HR of 2.94 (95% CI = 1.18–7.35, p = 0.0208) on D3. In addition, IbRiS yielded significant risk stratification within high ODx risk categories (D1 + D2: HR = 10.35, 95% CI = 1.20–89.18, p = 0.0106; D1: p = 0.0238; D2: p = 0.0389), potentially providing more granular risk stratification than offered by ODx alone.

Abstract Background Premature aging has been identified as a global risk factor for cancer. Causes of premature aging are multifactorial, including inflammation, infection, chronic stress, and lifestyle factors. Method We evaluated whether premature aging in people living with HIV (PLWH) was associated with antiretroviral therapy (ART) or the diagnosis of cancer. We used well‐established DNA methylation patterns to assess premature aging, using Horvath et al., in individuals with HIV located in Cleveland, Ohio and compared these to standardized datasets of US historical blood samples. Some of the PLWH developed cancer over time. Results We found that DNA methylation analysis identified accelerated aging in PLWH whereas ART therapy mitigated the advancement of DNA methylation age. A variety of cancers were observed in this population, but a cancer diagnosis was not significantly associated with more advanced DNA methylation age. Conclusion We find that the age acceleration detected in PLWH is mitigated by ART therapy and is not further accelerated by a diagnosis of cancer.

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.

Cord blood (CB) is a valuable graft source for patients undergoing allogeneic hematopoietic cell transplant (HCT) who lack human leukocyte antigen (HLA)-matched donors. However, single-unit CB-HCT is limited by the insufficient cell dose and slow engraftment. To overcome these limitations, we combined a single-unit CB with third-party healthy donors’ bone marrow (BM) derived mesenchymal stromal cells (MSCs) to improve engraftment and injected intra-osseously (IO) to enhance homing. In this phase I clinical trial, six patients with high-risk hematologic malignancies were enrolled and received allogeneic HCT using reduced intensity conditioning regimens. The primary objective was to determine the engraftment rate at day 42. The median age of enrolled patients was 68 years, and only one patient was in complete remission at the time of HCT. The median CB total nucleated cell dose was 3.2x107/kg. No serious adverse events were reported. Two patients had early deaths due to persistent disease and multi-drug resistant bacterial infection, respectively. Of the remaining four evaluable patients, all had successful neutrophil engraftment in a median of 17.5 days. No grade 3 or higher acute graft-versus-host disease (GvHD) was observed, and only one patient developed moderate-extensive chronic GvHD. In conclusion, IO co-transplantation of a single-unit CB and MSCs was feasible and resulted in a reasonable engraftment rate in these very high-risk patients.

Background: around one third of clinically significant prostate cancer (CsPCa) foci are reported to be MRI non-visible (MRI─). Objective: To quantify the differences between MR visible (MRI+) and MRI─ CsPCa using intra- and peri-lesional radiomic features on bi-parametric MRI (bpMRI). Methods: This retrospective and multi-institutional study comprised 164 patients with pre-biopsy 3T prostate multi-parametric MRI from 2014 to 2017. The MRI─ CsPCa referred to lesions with PI-RADS v2 score 1. Three experienced radiologists were involved in annotating lesions and PI-RADS assignment. The validation set (Dv) comprised 52 patients from a single institution, the remaining 112 patients were used for training (Dt). 200 radiomic features were extracted from intra-lesional and peri-lesional regions on bpMRI.Logistic regression with least absolute shrinkage and selection operator (LASSO) and 10-fold cross-validation was applied on Dt to identify radiomic features associated with MRI─ and MRI+ CsPCa to generate corresponding risk scores RMRI─ and RMRI+. RbpMRI was further generated by integrating RMRI─ and RMRI+. Statistical significance was determined using the Wilcoxon signed-rank test. Results: Both intra-lesional and peri-lesional bpMRI Haralick and CoLlAGe radiomic features were significantly associated with MRI─ CsPCa (p

IntroductionMedulloblastoma (MB) is a malignant, heterogenous brain tumor. Advances in molecular profiling have led to identifying four molecular subgroups of MB (WNT, SHH, Group 3, Group 4), each with distinct clinical behaviors. We hypothesize that (1) aggressive MB tumors, growing heterogeneously, induce pronounced local structural deformations in the surrounding parenchyma, and (b) these local deformations as captured on Gadolinium (Gd)-enhanced-T1w MRI are independently associated with molecular subgroups, as well as overall survival in MB patients.MethodsIn this work, a total of 88 MB studies from 2 institutions were analyzed. Following tumor delineation, Gd-T1w scan for every patient was registered to a normal age-specific T1w-MRI template via deformable registration. Following patient-atlas registration, local structural deformations in the brain parenchyma were obtained for every patient by computing statistics from deformation magnitudes obtained from every 5mm annular region, 0 < d < 60 mm, where d is the distance from the tumor infiltrating edge.ResultsMulti-class comparison via ANOVA yielded significant differences between deformation magnitudes obtained for Group 3, Group 4, and SHH molecular subgroups, observed up to 60-mm outside the tumor edge. Additionally, Kaplan-Meier survival analysis showed that the local deformation statistics, combined with the current clinical risk-stratification approaches (molecular subgroup information and Chang’s classification), could identify significant differences between high-risk and low-risk survival groups, achieving better performance results than using any of these approaches individually.DiscussionThese preliminary findings suggest there exists significant association of our tumor-induced deformation descriptor with overall survival in MB, and that there could be an added value in using the proposed radiomic descriptor along with the current risk classification approaches, towards more reliable risk assessment in pediatric MB.

Summary: Background: Hepatic steatosis (HS) identified on CT may provide an integrated cardiometabolic and COVID-19 risk assessment. This study presents a deep-learning-based hepatic fat assessment (DeHFt) pipeline for (a) more standardised measurements and (b) investigating the association between HS (liver-to-spleen attenuation ratio

Abstract Collagen fiber organization has been found to be implicated in breast cancer prognosis. In this study, we evaluated whether computerized features of Collagen Fiber Orientation Disorder in Tumor-associated Stroma (CFOD-TS) on Hematoxylin & Eosin (H&E) slide images were prognostic of Disease Free Survival (DFS) in early stage Estrogen Receptor Positive (ER+) Invasive Breast Cancers (IBC). A Cox regression model named MCFOD-TS, was constructed using cohort St (N = 78) to predict DFS based on CFOD-TS features. The prognostic performance of MCFOD-TS was validated on cohort Sv (N = 219), a prospective clinical trial dataset (ECOG 2197). MCFOD-TS was prognostic of DFS in both St and Sv, independent of clinicopathological variables. Additionally, the molecular pathways regarding cell cycle regulation were identified as being significantly associated with MCFOD-TS derived risk scores. Our results also found that collagen fiber organization was more ordered in patients with short DFS. Our study provided a H&E image-based pipeline to derive a potential prognostic biomarker for early stage ER+ IBC without the need of special collagen staining or advanced microscopy techniques.

BackgroundPrecision estimation of cardiovascular risk remains the cornerstone of atherosclerotic cardiovascular disease (ASCVD) prevention. While coronary artery calcium (CAC) scoring is the best available non-invasive quantitative modality to evaluate risk of ASCVD, it excludes risk related to prior myocardial infarction, cardiomyopathy, and arrhythmia which are implicated in ASCVD. The high-dimensional and inter-correlated nature of ECG data makes it a good candidate for analysis using machine learning techniques and may provide additional prognostic information not captured by CAC. In this study, we aimed to develop a quantitative ECG risk score (eRiS) to predict major adverse cardiovascular events (MACE) alone, or when added to CAC. Further, we aimed to construct and validate a novel nomogram incorporating ECG, CAC and clinical factors for ASCVD.MethodsWe analyzed 5,864 patients with at least 1 cardiovascular risk factor who underwent CAC scoring and a standard ECG as part of the CLARIFY study (ClinicalTrials.gov Identifier: NCT04075162). Events were defined as myocardial infarction, coronary revascularization, stroke or death. A total of 649 ECG features, consisting of measurements such as amplitude and interval measurements from all deflections in the ECG waveform (53 per lead and 13 overall) were automatically extracted using a clinical software (GE Muse™ Cardiology Information System, GE Healthcare). The data was split into 4 training (Str) and internal validation (Sv) sets [Str (1): Sv (1): 50:50; Str (2): Sv (2): 60:40; Str (3): Sv (3): 70:30; Str (4): Sv (4): 80:20], and the results were compared across all the subsets. We used the ECG features derived from Str to develop eRiS. A least absolute shrinkage and selection operator-Cox (LASSO-Cox) regularization model was used for data dimension reduction, feature selection, and eRiS construction. A Cox-proportional hazards model was used to assess the benefit of using an eRiS alone (Mecg), CAC alone (Mcac) and a combination of eRiS and CAC (Mecg+cac) for MACE prediction. A nomogram (Mnom) was further constructed by integrating eRiS with CAC and demographics (age and sex). The primary endpoint of the study was the assessment of the performance of Mecg, Mcac, Mecg+cac and Mnom in predicting CV disease-free survival in ASCVD.FindingsOver a median follow-up of 14 months, 494 patients had MACE. The feature selection strategy preserved only about 18% of the features that were consistent across the various strata (Str). The Mecg model, comprising of eRiS alone was found to be significantly associated with MACE and had good discrimination of MACE (C-Index: 0.7, p =

Introduction: Autoimmune disease has both a predisposing and a protective effect toward malignancy. Though studies have investigated the risk of malignancy in patients with autoimmune disease, there is limited research on how autoimmunity affects survival. Methods: This study compared survival in patients with lung cancer with and without autoimmune disease. Patients with lung cancer were culled from the Surveillance, Epidemiology, and End Results Medicare databases (2007–2014), and autoimmune diseases were identified using diagnosis codes. Results: The overall prevalence of investigated autoimmune diseases among the 112,445 patients was 22.7%. Overall survival (OS) (p < 0.0001) was longer and cancer-specific mortality (CSM) (p < 0.0001) reduced among patients with autoimmune disease. Median OS was 5 months higher. Improved OS and CSM were also apparent in disease stages 1, 3, and 4 in the NSCLC and SCLC subgroups (p < 0.0001) and across most specific autoimmune diseases. After adjusting for the effects of age, sex, race, disease stage, and chronic kidney disease, autoimmune disease was still predictive of higher OS (hazard ratio = 1.23, 95% confidence interval: 1.21–1.25, p < 0.0001) and reduced CSM (hazard ratio = 1.16, 95% confidence interval: 1.14–1.18, p < 0.0001). Conclusions: The prevalence of rheumatoid arthritis, inflammatory bowel disease, and systemic lupus erythematous was highly enriched compared with the general population. The improvement in OS and CSM was larger in NSCLC than in SCLC, suggesting a larger role for the immune system in NSCLC. Alternate explanations for the improved survival include lead time bias, better access to health care, and a survival or autoimmunity-inducing genetic factor.

Abstract Purpose Patients enrolled in Phase 1 clinical trials have typically exhausted standard therapies and often are choosing between a clinical trial and hospice care. Significant symptom burden can result in early trial discontinuation and confound trial outcomes. This study aimed to examine differences in study duration, symptom burden, adverse events (AE), and quality of life (QOL) between those receiving structured palliative care versus usual supportive care. Patients and methods Sixty‐eight patients enrolled in phase 1 clinical trials and 39 of their CGs were randomly assigned to receive structured palliative care or usual supportive care. Patient QOL was measured monthly using the Functional Assessment of Cancer Therapy and Memorial Symptom Assessment Scale. The Quality of Life in Life‐Threatening Illness–Family Care Version and Caregiver Reaction Assessment were used for CGs. AEs and use of palliative care resources were compared between arms. Results Mean duration of the phase 1 study was 142 days in the palliative care arm versus 116 days in the usual care arm (p = 0.55). Although not statistically significant, patients in the palliative care arm experienced fewer AEs and better QOL, as did their CGs, compared to those receiving usual care. Conclusions Phase 1 patients and their CGs have physical and psychosocial needs warranting palliative care services. Results suggest that structured palliative care is associated with the increased duration of the study and improved patient and CG QOL.

Abstract Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p

Abstract Background Lymphopenia can decrease immune function of the host and is a known risk factor for poor prognosis in malignant tumors. Radiation induced lymphopenia was common in patients with breast cancer and was also reported to have a negative effect on long‐term outcome. Aims Lymphopenia may be associated with baseline immune status before radiotherapy (RT). This study aimed to explore the rate and risk factors of lymphopenia before start of the adjuvant RT in patients with breast cancer. Methods Patients with invasive breast cancer treated from March 2015 to February 2020 and with peripheral lymphocyte counts (PLC) available within 7 days from the beginning of RT were eligible for this study. Data were presented as mean and 95% confidence interval unless otherwise specified. The risk factors of low PLC before RT were identified using univariate and multivariable linear regressions. Results A total of 1012 consecutive patients met the study criteria. The mean PLC before RT commencement was 1.58*109/L (95%CI: 1.55–1.62*109/L) with 15.2% (95%CI: 13.1%–17.6%) CTCAE defined lymphopenia, rendering 12.3%, 2.6%, 0.3%, and 0% for grade 1, 2, 3 and 4 respectively. Univariate and multivariable linear regression showed prior chemotherapy was the most significant risk factor (p .05). A total of 912 (90.1%, 95%CI: 88.1%–91.9%) patients had chemotherapy before adjuvant RT in this study. In patients with HR+/HER2‐ breast cancer, 69.0% (95%CI: 63.0%–74.5%) N0 and 98.1% (95%CI: 95.1%–99.5%) N1 had also received chemotherapy. Conclusions Patients with breast cancer might have lymphopenia from prior chemotherapy at the start of adjuvant RT which could have negative effect on long‐term outcome. It is also noted that most of the patients with HR+/HER2‐, early‐stage breast cancer were treated with aggressive chemotherapy without knowing the risk of chemotherapy induced lymphopenia. Future study on predictive or prognostic multigene assays is warranted to avoid unnecessary chemotherapy and subsequent lymphopenia in patients with low risk breast cancer.

ObjectiveTo derive and evaluate the association of prostate shape distension descriptors from T2-weighted MRI (T2WI) with prostate cancer (PCa) biochemical recurrence (BCR) post-radical prostatectomy (RP) independently and in conjunction with texture radiomics of PCa.MethodsThis retrospective study comprised 133 PCa patients from two institutions who underwent 3T-MRI prior to RP and were followed up with PSA measurements for ≥3 years. A 3D shape atlas-based approach was adopted to derive prostate shape distension descriptors from T2WI, and these descriptors were used to train a random forest classifier (CS) to predict BCR. Texture radiomics was derived within PCa regions of interest from T2WI and ADC maps, and another machine learning classifier (CR) was trained for BCR. An integrated classifier CS+R was then trained using predictions from CS and CR. These models were trained on D1 (N = 71, 27 BCR+) and evaluated on independent hold-out set D2 (N = 62, 12 BCR+). CS+R was compared against pre-RP, post-RP clinical variables, and extant nomograms for BCR-free survival (bFS) at 3 years.ResultsCS+R resulted in a higher AUC (0.75) compared to CR (0.70, p = 0.04) and CS (0.69, p = 0.01) on D2 in predicting BCR. On univariable analysis, CS+R achieved a higher hazard ratio (2.89, 95% CI 0.35–12.81, p < 0.01) compared to other pre-RP clinical variables for bFS. CS+R, pathologic Gleason grade, extraprostatic extension, and positive surgical margins were associated with bFS (p < 0.05). CS+R resulted in a higher C-index (0.76 ± 0.06) compared to CAPRA (0.69 ± 0.09, p < 0.01) and Decipher risk (0.59 ± 0.06, p < 0.01); however, it was comparable to post-RP CAPRA-S (0.75 ± 0.02, p = 0.07).ConclusionsRadiomic shape descriptors quantifying prostate surface distension complement texture radiomics of prostate cancer on MRI and result in an improved association with biochemical recurrence post-radical prostatectomy.

ObjectiveThe disease COVID-19 has caused a widespread global pandemic with ~3. 93 million deaths worldwide. In this work, we present three models—radiomics (MRM), clinical (MCM), and combined clinical–radiomics (MRCM) nomogram to predict COVID-19-positive patients who will end up needing invasive mechanical ventilation from the baseline CT scans.MethodsWe performed a retrospective multicohort study of individuals with COVID-19-positive findings for a total of 897 patients from two different institutions (Renmin Hospital of Wuhan University, D1 = 787, and University Hospitals, US D2 = 110). The patients from institution-1 were divided into 60% training, D1T (N = 473), and 40% test set D1V (N = 314). The patients from institution-2 were used for an independent validation test set D2V (N = 110). A U-Net-based neural network (CNN) was trained to automatically segment out the COVID consolidation regions on the CT scans. The segmented regions from the CT scans were used for extracting first- and higher-order radiomic textural features. The top radiomic and clinical features were selected using the least absolute shrinkage and selection operator (LASSO) with an optimal binomial regression model within D1T.ResultsThe three out of the top five features identified using D1T were higher-order textural features (GLCM, GLRLM, GLSZM), whereas the last two features included the total absolute infection size on the CT scan and the total intensity of the COVID consolidations. The radiomics model (MRM) was constructed using the radiomic score built using the coefficients obtained from the LASSO logistic model used within the linear regression (LR) classifier. The MRM yielded an area under the receiver operating characteristic curve (AUC) of 0.754 (0.709–0.799) on D1T, 0.836 on D1V, and 0.748 D2V. The top prognostic clinical factors identified in the analysis were dehydrogenase (LDH), age, and albumin (ALB). The clinical model had an AUC of 0.784 (0.743–0.825) on D1T, 0.813 on D1V, and 0.688 on D2V. Finally, the combined model, MRCM integrating radiomic score, age, LDH and ALB, yielded an AUC of 0.814 (0.774–0.853) on D1T, 0.847 on D1V, and 0.771 on D2V. The MRCM had an overall improvement in the performance of ~5.85% (D1T: p = 0.0031; D1Vp = 0.0165; D2V: p = 0.0369) over MCM.ConclusionThe novel integrated imaging and clinical model (MRCM) outperformed both models (MRM) and (MCM). Our results across multiple sites suggest that the integrated nomogram could help identify COVID-19 patients with more severe disease phenotype and potentially require mechanical ventilation.

BackgroundLymphopenia is a known significant factor for treatment outcome in cancer patients, with underlying risk factor poorly understood in breast cancer. We hypothesize that the effective dose to the circulating immune cells (EDIC) which was related with lymphopenia in lung cancer will also have significant effect for radiation induced lymphopenia (RIL) in patients with breast cancer.Material and MethodsPatients treated with adjuvant radiotherapy (RT) and with complete blood tests within one week from RT end/start (post/preRT) were eligible in this study. Radiation dosimetric factors were collected retrospectively, and EDIC for each patient was calculated based on the doses to lung, heart and total body according to the model description, as previously reported. RIL was defined by the CTCAE5.0 based on postRT peripheral lymphocyte count (PLC). Linear regression was first used to test the correlation between EDIC with post/preRT PLC ratio and postRT PLC, using all these as continuous variables. Normal tissue complication probability (NTCP) was used to develop models that predict the CTCAE graded RIL from EDIC.ResultsA total of 735 patients were eligible. The mean post/preRT PLC ratio was 0.66 (95% CI: 0.64-0.68) and mean EDIC of breast cancer was 1.70Gy (95% CI: 1.64-1.75). Both post/preRT PLC ratio and postRT PLC were significantly correlated with EDIC (P

Background The landmark study of durvalumab as consolidation therapy in NSCLC patients (PACIFIC trial) demonstrated significantly longer progression-free survival (PFS) in patients with locally advanced, unresectable non-small cell lung cancer (NSCLC) treated with durvalumab (immunotherapy, IO) therapy after chemoradiotherapy (CRT). In clinical practice in the USA, durvalumab continues to be used in patients across all levels of programmed cell death ligand-1 (PD-L1) expression. While immune therapies have shown promise in several cancers, some patients either do not respond to the therapy or have cancer recurrence after an initial response. It is not clear so far who will benefit of this therapy or what the mechanisms behind treatment failure are.Methods A total of 133 patients with unresectable stage III NSCLC who underwent durvalumab after CRT or CRT alone were included. Patients treated with durvalumab IO after CRT were randomly split into training (D1=59) and test (D2=59) sets and the remaining 15 patients treated with CRT alone were grouped in D3. Radiomic textural patterns from within and around the target nodules were extracted. A radiomic risk score (RRS) was built and was used to predict PFS and overall survival (OS). Patients were divided into high-risk and low-risk groups based on median RRS.Results RRS was found to be significantly associated with PFS in D1 (HR=2.67, 95% CI 1.85 to 4.13, p

PurposeApplication of hypofractionated radiotherapy (HFRT) is growing in patients with breast cancer (BC). This study aimed to explore a real-world practice of HFRT in early and locally advanced BC.MethodsPatients with invasive BC between 2015 and 2019 were retrospectively reviewed. Radiotherapy (RT) was delivered by HFRT and conventionally fractionated radiotherapy (CFRT). Locoregional recurrence-free survival (LRRFS) and disease-free survival (DFS) were calculated by Kaplan–Meier curve and compared by Log-rank test. The effect of treatment modality on DFS was estimated by univariate and multivariable analyses.ResultsA total of 1,010 patients were included in this study, and 903 (89.4%) were treated with HFRT. At a median follow-up of 49.5 months, there was no significant difference in a 4-year cumulative incidence of LRRFS in HFRT group (1.5%) and in CFRT group (3.8%) (p = 0.23), neither in different nodal stages nor in N2–3 patients with different molecular subtypes. The 4-year DFS was 93.5% in HFRT group compared with 89.9% in CFRT group with no significant difference either (p = 0.17). Univariate and multivariable analyses also showed no significant difference in DFS between HFRT and CFRT group. However, DFS of HFRT group tended to be lower in N2–3 patients with triple negative BC compared with that of CFRT group (76.2% versus 100%).ConclusionHFRT can achieve similar cumulative incidence of LRRFS and DFS in patients with BC after lumpectomy or mastectomy, and also in different nodal stage, and in locally advanced stage with different molecular subtypes.

Background We present a computational approach (ArcTIL) for quantitative characterization of the architecture of tumor-infiltrating lymphocytes (TILs) and their interplay with cancer cells from digitized H&E-stained histology whole slide images and evaluate its prognostic role in three different gynecological cancer (GC) types and across three different treatment types (platinum, radiation and immunotherapy).Methods In this retrospective study, we included 926 patients with GC diagnosed with ovarian cancer (OC), cervical cancer, and endometrial cancer with available digitized diagnostic histology slides and survival outcome information. ArcTIL features quantifying architecture and spatial interplay between immune cells and the rest of nucleated cells (mostly comprised cancer cells) were extracted from the cell cluster graphs of nuclei within the tumor epithelial nests, surrounding stroma and invasive tumor front compartments on H&E-stained slides. A Cox proportional hazards model, incorporating ArcTIL features was fit on the OC training cohort (N=51), yielding an ArcTIL signature. A unique threshold learned from the training set stratified the patients into a low and high-risk group.Results The seven feature ArcTIL classifier was found to significantly correlate with overall survival in chemotherapy and radiotherapy-treated validation cohorts and progression-free survival in an immunotherapy-treated validation cohort. ArcTIL features relating to increased density of TILs in the epithelium and invasive tumor front were found to be associated with better survival outcomes when compared with those patients with an increased TIL density in the stroma. A statistically significant association was found between the ArcTIL signature and signaling pathways for blood vessel morphogenesis, vasculature development, regulation of cell differentiation, cell-substrate adhesion, biological adhesion, regulation of vasculature development, and angiogenesis.Conclusions This study reveals that computationally-derived features from the spatial architecture of TILs and tumor cells are prognostic in GCs treated with chemotherapy, radiotherapy, and checkpoint blockade and are closely associated with central biological processes that impact tumor progression. These findings could aid in identifying therapy-refractory patients and further enable personalized treatment decision-making.

BackgroundSmall cell lung cancer (SCLC) is an aggressive malignancy characterized by initial chemosensitivity followed by resistance and rapid progression. Presently, there are no predictive biomarkers that can accurately guide the use of systemic therapy in SCLC patients. This study explores the role of radiomic features from both within and around the tumor lesion on pretreatment CT scans to a) prognosticate overall survival (OS) and b) predict response to chemotherapy.MethodsOne hundred fifty-three SCLC patients who had received chemotherapy were included. Lung tumors were contoured by an expert reader. The patients were divided randomly into approximately equally sized training (Str = 77) and test sets (Ste = 76). Textural descriptors were extracted from the nodule (intratumoral) and parenchymal regions surrounding the nodule (peritumoral). The clinical endpoints of this study were OS, progression-free survival (PFS), and best objective response to chemotherapy. Patients with complete or partial response were defined as “responders,” and those with stable or progression of disease were defined as “non-responders.” The radiomic risk score (RRS) was generated by using the least absolute shrinkage and selection operator (LASSO) with the Cox regression model. Patients were classified into the high-risk or low-risk groups based on the median of RRS. Association of the radiomic signature with OS was evaluated on Str and then tested on Ste. The features identified by LASSO were then used to train a linear discriminant analysis (LDA) classifier (MRad) to predict response to chemotherapy. A prognostic nomogram (NRad+Clin) was also developed on Str by combining clinical and prognostic radiomic features and validated on Ste. The Kaplan–Meier survival analysis and log-rank statistical tests were performed to assess the discriminative ability of the features. The discrimination performance of the NRad+Clin was assessed by Harrell’s C-index. To estimate the clinical utility of the nomogram, decision curve analysis (DCA) was performed by calculating the net benefits for a range of threshold probabilities in predicting which high-risk patients should receive more aggressive treatment as compared with the low-risk patients.ResultsA univariable Cox regression analysis indicated that RRS was significantly associated with OS in Str (HR: 1.53; 95% CI, [1.1–2.2; p = 0.021]; C-index = 0.72) and Ste (HR: 1.4, [1.1–1.82], p = 0.0127; C-index = 0.69). The RRS was also significantly associated with PFS in Str (HR: 1.89, [1.4–4.61], p = 0.047; C-index = 0.7) and Ste (HR: 1.641, [1.1–2.77], p = 0.04; C-index = 0.67). MRad was able to predict response to chemotherapy with an area under the receiver operating characteristic curve (AUC) of 0.76 ± 0.03 within Str and 0.72 within Ste. Predictors, including the RRS, gender, age, stage, and smoking status, were used in the prognostic nomogram. The discrimination ability of the NRad+Clin model on Str and Ste was C-index [95% CI]: 0.68 [0.66–0.71] and 0.67 [0.63–0.69], respectively. DCA indicated that the NRad+Clin model was clinically useful.ConclusionsRadiomic features extracted within and around the lung tumor on CT images were both prognostic of OS and predictive of response to chemotherapy in SCLC patients.

PurposeThere is a lack of biomarkers for accurately prognosticating outcome in both human papillomavirus-related (HPV+) and tobacco- and alcohol-related (HPV−) oropharyngeal squamous cell carcinoma (OPSCC). The aims of this study were to i) develop and evaluate radiomic features within (intratumoral) and around tumor (peritumoral) on CT scans to predict HPV status; ii) investigate the prognostic value of the radiomic features for both HPV− and HPV+ patients, including within individual AJCC eighth edition-defined stage groups; and iii) develop and evaluate a clinicopathologic imaging nomogram involving radiomic, clinical, and pathologic factors for disease-free survival (DFS) prediction for HPV+ patients.Experimental DesignThis retrospective study included 582 OPSCC patients, of which 462 were obtained from The Cancer Imaging Archive (TCIA) with available tumor segmentation and 120 were from Cleveland Clinic Foundation (CCF, denoted as SCCF) with HPV+ OPSCC. We subdivided the TCIA cohort into training (ST, 180 patients) and validation (SV, 282 patients) based on an approximately 3:5 ratio for HPV status prediction. The top 15 radiomic features that were associated with HPV status were selected by the minimum redundancy–maximum relevance (MRMR) using ST and evaluated on SV. Using 3 of these 15 top HPV status-associated features, we created radiomic risk scores for both HPV+ (RRSHPV+) and HPV− patients (RRSHPV−) through a Cox regression model to predict DFS. RRSHPV+ was further externally validated on SCCF. Nomograms for the HPV+ population (Mp+RRS) were constructed. Both RRSHPV+ and Mp+RRS were used to prognosticate DFS for the AJCC eighth edition-defined stage I, stage II, and stage III patients separately.ResultsRRSHPV+ was prognostic for DFS for i) the whole HPV+ population [hazard ratio (HR) = 1.97, 95% confidence interval (CI): 1.35–2.88, p < 0.001], ii) the AJCC eighth stage I population (HR = 1.99, 95% CI: 1.04–3.83, p = 0.039), and iii) the AJCC eighth stage II population (HR = 3.61, 95% CI: 1.71–7.62, p < 0.001). HPV+ nomogram Mp+RRS (C-index, 0.59; 95% CI: 0.54–0.65) was also prognostic of DFS (HR = 1.86, 95% CI: 1.27–2.71, p = 0.001).ConclusionCT-based radiomic signatures are associated with both HPV status and DFS in OPSCC patients. With additional validation, the radiomic signature and its corresponding nomogram could potentially be used for identifying HPV+ OPSCC patients who might be candidates for therapy deintensification.

Abstract The retinoblastoma gene (RB1) encodes the retinoblastoma (RB) pocket protein that plays an important role in cell cycle progression. Here we determine the frequency and prognostic significance of RB1 mutation in non small cell lung cancer (NSCLC), restricting inclusion to Stage III and IV patients with linked genomic and clinical data. The primary outcome was median overall survival (OS). We identified RB1 mutation in 8.2% of NSCLC patients. The median OS for wild‐type (wt) RB1 was 28.3 months vs 8.3 months for mutant RB1 (Hazard Ratio = 2.59, P = 0.002). Of special interest, RB1 mutation also correlated with lack of response to immunotherapy. Our study focused on RB1 mutation in locally advanced and advanced non small cell lung cancer to better facilitate comparisons with small cell lung cancer (SCLC). In our SCLC cohort, RB1 mutation was identified in 75% of patients and wt RB1 was associated with significantly shorter OS (P = 0.002). The different outcomes of RB1 mutation observed among lung cancer subtypes suggest a more complicated mechanism than simple regulation of cell cycle or response to chemotherapy.

Summary: Background: Biparametric MRI (comprising T2-weighted MRI and apparent diffusion coefficient maps) is increasingly being used to characterise prostate cancer. Although previous studies have combined Prostate Imaging–Reporting & Data System (PI-RADS)-based MRI findings with routinely available clinical variables and with deep learning-based imaging predictors, respectively, for prostate cancer risk stratification, none have combined all three. We aimed to construct an integrated nomogram (referred to as ClaD) combining deep learning-based imaging predictions, PI-RADS scoring, and clinical variables to identify clinically significant prostate cancer on biparametric MRI. Methods: In this retrospective multicentre study, we included patients with prostate cancer, with histopathology or biopsy reports and a screening or diagnostic MRI scan in the axial view, from four cohorts in the USA (from University Hospitals Cleveland Medical Center, Icahn School of Medicine at Mount Sinai, Cleveland Clinic, and Long Island Jewish Medical Center) and from the PROSTATEx Challenge dataset in the Netherlands. We constructed an integrated nomogram combining deep learning, PI-RADS score, and clinical variables (prostate-specific antigen, prostate volume, and lesion volume) using multivariable logistic regression to identify clinically significant prostate cancer on biparametric MRI. We used data from the first three cohorts to train the nomogram and data from the remaining two cohorts for independent validation. We compared the performance of our ClaD integrated nomogram with that of integrated nomograms combining clinical variables with either the deep learning-based imaging predictor (referred to as DIN) or PI-RADS score (referred to as PIN) using area under the receiver operating characteristic curves (AUCs). We also compared the ability of the nomograms to predict biochemical recurrence on a subset of patients who had undergone radical prostatectomy. We report cross-validation AUCs as means for the training set and used AUCs with 95% CIs to assess the performance on the test set. The difference in AUCs between the models were tested for statistical significance using DeLong's test. We used log-rank tests and Kaplan-Meier curves to analyse survival. Findings: We investigated 592 patients (823 lesions) with prostate cancer who underwent 3T multiparametric MRI at five hospitals in the USA between Jan 8, 2009, and June 3, 2017. The training data set consisted of 368 patients from three sites (the PROSTATEx Challenge cohort [n=204], University Hospitals Cleveland Medical Center [n=126], and Icahn School of Medicine at Mount Sinai [n=38]), and the independent validation data set consisted of 224 patients from two sites (Cleveland Clinic [n=151] and Long Island Jewish Medical Center [n=73]). The ClaD clinical nomogram yielded an AUC of 0·81 (95% CI 0·76–0·85) for identification of clinically significant prostate cancer in the validation data set, significantly improving performance over the DIN (0·74 [95% CI 0·69–0·80], p=0·0005) and PIN (0·76 [0·71–0·81], p

Background: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). Methods: 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. Findings: CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D3 (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR = 1.41, adj. P < .001) and D3 (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR = 0.42, adj. P = .006) and D3 (HR = 0.46, adj. P = .08). Interpretation: CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients.

Background: We developed and validated an integrated radiomic-clinicopathologic nomogram (RadClip) for post-surgical biochemical recurrence free survival (bRFS) and adverse pathology (AP) prediction in men with prostate cancer (PCa). RadClip was further compared against extant prognostics tools like CAPRA and Decipher. Methods: A retrospective study of 198 patients with PCa from four institutions who underwent pre-operative 3 Tesla MRI followed by radical prostatectomy, between 2009 and 2017 with a median 35-month follow-up was performed. Radiomic features were extracted from prostate cancer regions on bi-parametric magnetic resonance imaging (bpMRI). Cox Proportional-Hazards (CPH) model warped with minimum redundancy maximum relevance (MRMR) feature selection was employed to select bpMRI radiomic features for bRFS prediction in the training set (D1, N = 71). In addition, a bpMRI radiomic risk score (RadS) and associated nomogram, RadClip, were constructed in D1 and then compared against the Decipher, pre-operative (CAPRA), and post-operative (CAPRA-S) nomograms for bRFS and AP prediction in the testing set (D2, N = 127). Findings: “RadClip yielded a higher C-index (0.77, 95% CI 0.65-0.88) compared to CAPRA (0.68, 95% CI 0.57-0.8) and Decipher (0.51, 95% CI 0.33-0.69) and was found to be comparable to CAPRA-S (0.75, 95% CI 0.65-0.85). RadClip resulted in a higher AUC (0.71, 95% CI 0.62-0.81) for predicting AP compared to Decipher (0.66, 95% CI 0.56-0.77) and CAPRA (0.69, 95% CI 0.59-0.79).” Interpretation: RadClip was more prognostic of bRFS and AP compared to Decipher and CAPRA. It could help pre-operatively identify PCa patients at low risk of biochemical recurrence and AP and who therefore might defer additional therapy. Funding: The National Institutes of Health, the U.S. Department of Veterans Affairs, and the Department of Defense.

Background: Immune thrombotic thrombocytopenic purpura (iTTP) is a rare, life-threatening disorder managed with plasma exchange (PLEX) and steroids. Addition of rituximab (RTX) to initial disease treatment has been shown to lower future relapse rates. Information as to whether upfront cyclophosphamide (CTX) treatment is helpful in reducing relapse is not known.Methods: In a retrospective cohort study, we identified all patients at our institution diagnosed with iTTP between 2010 and 2019. We analyzed outcomes of cumulative incidence of relapse (CIR) and duration of remission.Results: Thirty Nine patients were studied. Group A (n = 10) included patients who received upfront PLEX and steroids alone, and Group B (n = 28) included those who received either upfront RTX (n = 23) or CTX (n = 5) in addition to PLEX and steroids. The 2-year CIR was 50% in Group A and 27.7% in Group B, with a median duration of remission of 43.6 months vs. 108.3 months, respectively (p = 0.04). Group A was associated with a HR=8.7 (95% CI: 1.27, 59.45), p = 0.027 for duration of remission. There was no significant difference between CTX and RTX in both outcomes of CIR and duration of remission. We observed a potential impact on remission duration based on the presenting absolute neutrophil count (HR = 0.74, 95% CI: 0.58, 0.96) and serum creatinine (HR = 1.42, 95% CI: 1.03, 1.94).Conclusion: There was no significant difference in iTTP relapse outcomes between upfront RTX and CTX. Absolute neutrophil count and serum creatinine may have a role in predicting relapse. Larger, prospective studies are needed to evaluate these findings.

Summary: Background: Use of adjuvant chemotherapy in patients with early-stage lung cancer is controversial because no definite biomarker exists to identify patients who would receive added benefit from it. We aimed to develop and validate a quantitative radiomic risk score (QuRiS) and associated nomogram (QuRNom) for early-stage non-small cell lung cancer (NSCLC) that is prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy following surgery. Methods: We did a retrospective multicohort study of individuals with early-stage NSCLC (stage I and II) who either received surgery alone or surgery plus adjuvant chemotherapy. We selected patients for whom we had available pre-treatment diagnostic CT scans and corresponding survival information. We used radiomic texture features derived from within and outside the primary lung nodule on chest CT scans of patients from the Cleveland Clinic Foundation (Cleveland, OH, USA; cohort D1) to develop QuRiS. A least absolute shrinkage and selection operator-Cox regularisation model was used for data dimension reduction, feature selection, and QuRiS construction. QuRiS was independently validated on a cohort of patients from the University of Pennsylvania (Philadephia, PA, USA; cohort D2) and a cohort of patients whose CT scans were derived from The Cancer Imaging Archive (cohort D3). QuRNom was constructed by integrating QuRiS with tumour and node descriptors (according to the tumour, node, metastasis staging system) and lymphovascular invasion. The primary endpoint of the study was the assessment of the performance of QuRiS and QuRNom in predicting disease-free survival. The added benefit of adjuvant chemotherapy estimated using QuRiS and QuRNom was validated by comparing patients who received adjuvant chemotherapy versus patients who underwent surgery alone in cohorts D1–D3. Findings: We included: 329 patients in cohort D1 (73 [22%] had surgery plus adjuvant chemotherapy and 256 (78%) had surgery alone); 114 patients in cohort D2 (33 [29%] had surgery plus adjuvant chemotherapy and 81 (71%) had surgery alone); and 82 patients in cohort D3 (24 [29%] had surgery plus adjuvant chemotherapy and 58 (71%) had surgery alone). QuRiS comprised three intratumoral and 10 peritumoral CT-radiomic features and was found to be significantly associated with disease-free survival (ie, prognostic validation of QuRiS; hazard ratio for predicted high-risk vs predicted low-risk groups 1·56, 95% CI 1·08–2·23, p=0·016 for cohort D1; 2·66, 1·24–5·68, p=0·011 for cohort D2; and 2·67, 1·39–5·11, p=0·0029 for cohort D3). To validate the predictive performance of QuRiS, patients were partitioned into three risk groups (high, intermediate, and low risk) on the basis of their corresponding QuRiS. Patients in the high-risk group were observed to have significantly longer survival with adjuvant chemotherapy than patients who underwent surgery alone (0·27, 0·08–0·95, p=0·042, for cohort D1; 0·08, 0·01–0·42, p=0·0029, for cohorts D2 and D3 combined). As concerns QuRNom, the nomogram-estimated survival benefit was predictive of the actual efficacy of adjuvant chemotherapy (0·25, 0·12–0·55, p

The oxidant/antioxidant balance has been implicated in the pathophysiology of prostate cancer. We investigated oxidative damage and antioxidant status in high-risk prostate cancer subjects. Reduced glutathione (GSH) levels were measured in erythrocytes, 8-hydroxydeoxyguanosine (8-OHdG) in leukocytes and plasma levels of catalase (CAT), glutathione peroxidase (GSH-Px), glutathione reductase (GSH-R), glutathione S-transferase (GST), superoxide dismutase (SOD), and lipid peroxide products were measured in high-risk and age-matched healthy subjects. Serum PSA levels were significantly higher (p < 0.0001) in high-risk subjects, whereas GST (p < 0.0001) and GSH (p < 0.002) were higher in healthy controls. Levels of 8-OHdG, an oxidized nucleoside of DNA, were significantly increased (p < 0.0001) in high-risk subjects. No marked difference in the levels of CAT (p = 0.237), GSH-Px (p = 0.74), GSH-R (p = 0.344), SOD (p = 0.109), and lipid peroxide products (p = 0129) were observed between two groups. Pearson’s correlation between GST and PSA (r = −0.69 (p < 0.0001)), GST and 8-OHdG (r = −0.62 (p < 0.0004)), GSH and 8-OHdG (r= −0.39 (p = 0.038)), and CAT and GSH-Px (r= −0.33 (p = 0.04)) were found to be negatively correlated, whereas 8-OHdG and PSA were positively associated (r= 0.57 (p < 0.002). These results indicate a significant role of oxidative damage in prostate carcinogenesis, particularly during the early stages of development. In conclusion, our data support the importance of antioxidant defense as a valuable diagnostic and/or prognostic marker in prostate cancer.

Translation of radiomics into the clinic may require a more comprehensive understanding of the underlying morphologic tissue characteristics they reflect. In the context of prostate cancer (PCa), some studies have correlated gross histological measurements of gland lumen, epithelium, and nuclei with disease appearance on MRI. Quantitative histomorphometry (QH), like radiomics for radiologic images, is the computer based extraction of features for describing tumor morphology on digitized tissue images. In this work, we attempt to establish the histomorphometric basis for radiomic features for prostate cancer by (1) identifying the radiomic features from T2w MRI most discriminating of low vs. intermediate/high Gleason score, (2) identifying QH features correlated with the most discriminating radiomic features previously identified, and (3) evaluating the discriminative ability of QH features found to be correlated with spatially co-localized radiomic features. On a cohort of 36 patients (23 for training, 13 for validation), Gabor texture features were identified as being most predictive of Gleason grade on MRI (AUC of 0.69) and gland lumen shape features were identified as the most predictive QH features (AUC = 0.75). Our results suggest that the PCa grade discriminability of Gabor features is a consequence of variations in gland shape and morphology at the tissue level.

Aberrant nuclear factor-κB (NF-κB) activation has been implicated in the pathogenesis of several human malignancies. In this study, we determined whether NF-κB is constitutively activated in human prostate adenocarcinoma, and, if so, whether increased NF-κB activation and its binding to DNA influence tumor progression. Using tissue samples obtained during transurethral prostatic resection and paraffin-embedded sections of benign and cancer specimens, we determined the nuclear expression of NF-κB/p65 and NF-κB/p50, cytoplasmic expression of IκBα, its phosphorylation, and expression of NF-κB-regulated genes, specifically Bcl2, cyclin D1, matrix metalloproteinase-9 (MMP-9), and vascular endothelial growth factor (VEGF). A progressive increase in the expression of NF-κB/p65 (but not of p50) was observed in cancer specimens compared to benign tissue, which correlated with increasing levels of IκBa and its phosphorylation. NF-κB DNA-binding activity increased with increasing tumor grade and the binding complex mainly consisted of NF-κB/p65-p50 heterodimers. Immunohistochemical analysis showed enhanced nuclear staining for NF-κB/p65 in both high-grade (P < .0001) and low-grade (P < .003) cancer specimens, compared to benign tissue. The nuclear levels of NF-κB/p65 correlated with concurrent increase in cytosolic levels of IκBa along with NF-κB-dependent expression of Bcl2, cyclin D1, MMP-9, and VEGF. These results demonstrate that NF-κB/p65 is constitutively activated in human prostate adenocarcinoma and is related to tumor progression due to transcriptional regulation of NF-κB-responsive genes.

Aberrant Nuclear Factor-κappaB (NF-κB) activation due to rapid IκBα turnover and high basal IκBα kinase (IKK) activity has been frequently observed in prostate cancer. Apigenin, a naturally occurring plant flavone, exhibits anti-proliferative, anti-inflammatory and anti-carcinogenic activities by inhibiting NF-κB pathway, through a mechanism not fully understood. We found that apigenin feeding in microgram doses (bioavailable in humans) inhibited prostate tumorigenesis in TRAMP mice by interfering with NF-κB signaling. Apigenin feeding to TRAMP mice (20 and 50 μg/mouse/day, 6 days/week for 20 weeks) exhibited significant decrease in tumor volumes of the prostate and completely abolished metastasis, which correlated with inhibition of NF-κB activation and binding to the DNA. Apigenin intake blocked phosphorylation and degradation of IκBα by inhibiting IKK activation, which in turn led to suppression of NF-κB activation. The expression of NF-κB-regulated gene products involved in proliferation (cyclin D1, and COX-2), anti-apoptosis (Bcl-2 and Bcl-xL), and angiogenesis (vascular endothelial growth factor) were also downregulated after apigenin feeding. These events correlated with the induction of apoptosis in tumor cells, as evident by increased cleaved caspase-3 labeling index in the dorsolateral prostate. Our results provide convincing evidence that apigenin inhibits IKK activation and restores the expression of IκBα, preventing it's phosphorylation in a fashion similar to that elicited by IKK and proteasomal inhibitors through suppression of NF-κB signaling pathway.

Effective antiretroviral therapy (ART) dramatically reduces AIDS-related complications, yet the life expectancy of long-term ART-treated HIV-infected patients remains shortened compared to that of uninfected controls, due to increased risk of non-AIDS related morbidities. Many propose that these complications result from translocated microbial products from the gut that stimulate systemic inflammation--a consequence of increased intestinal paracellular permeability that persists in this population. Concurrent intestinal immunodeficiency and structural barrier deterioration are postulated to drive microbial translocation, and direct evidence of intestinal epithelial breakdown has been reported in untreated pathogenic SIV infection of rhesus macaques. To assess and characterize the extent of epithelial cell damage in virally-suppressed HIV-infected patients, we analyzed intestinal biopsy tissues for changes in the epithelium at the cellular and molecular level. The intestinal epithelium in the HIV gut is grossly intact, exhibiting no decreases in the relative abundance and packing of intestinal epithelial cells. We found no evidence for structural and subcellular localization changes in intestinal epithelial tight junctions (TJ), but observed significant decreases in the colonic, but not terminal ileal, transcript levels of TJ components in the HIV+ cohort. This result is confirmed by a reduction in TJ proteins in the descending colon of HIV+ patients. In the HIV+ cohort, colonic TJ transcript levels progressively decreased along the proximal-to-distal axis. In contrast, expression levels of the same TJ transcripts stayed unchanged, or progressively increased, from the proximal-to-distal gut in the healthy controls. Non-TJ intestinal epithelial cell-specific mRNAs reveal differing patterns of HIV-associated transcriptional alteration, arguing for an overall change in intestinal epithelial transcriptional regulation in the HIV colon. These findings suggest that persistent intestinal epithelial dysregulation involving a reduction in TJ expression is a mechanism driving increases in colonic permeability and microbial translocation in the ART-treated HIV-infected patient, and a possible immunopathogenic factor for non-AIDS related complications.

BackgroundDelayed chemotherapy is associated with inferior survival in stage III colon and stage II/III rectal cancer patients, but similar studies have not been performed in stage II colon cancer patients. We investigate the association between delayed and incomplete chemotherapy, and the association of delayed chemotherapy with survival in stage II colon cancer patients.Patients and methodsPatients (age ≥ 66) diagnosed as stage II colon cancer and received chemotherapy from 1992 to 2005 were identified from the linked SEER-Medicare database. The association between delayed and incomplete chemotherapy was assessed using unconditional and conditional logistic regressions. Survival outcomes were assessed using stratified Cox regression based on propensity score matched samples.Results4,209 stage II colon cancer patients were included, of whom 73.0% had chemotherapy initiated timely (≤ 2 months after surgery), 14.7% had chemotherapy initiated with moderate delay (2-3 months), and 12.3% had delayed chemotherapy (≥ 3 months). Delayed chemotherapy was associated with not completing chemotherapy (adjusted odds ratio (OR): 1.33 (95% confidence interval: 1.11, 1.59) for moderately delayed group, adjusted OR: 2.60 (2.09, 3.24) for delayed group). Delayed chemotherapy was associated with worse survival outcomes (hazard ratio (HR): 1.75 (1.29, 2.37) for overall survival; HR: 4.23 (2.19, 8.20) for cancer-specific survival).ConclusionAlthough the benefit of chemotherapy is unclear in stage II colon cancer patients, delay in initiation of chemotherapy is associated with an incomplete chemotherapy course and poorer survival, especially cancer-specific survival. Causal inference in the association between delayed initiation of chemotherapy and inferior survival requires further investigation.

Targeting most-at-risk individuals with HIV preventive interventions is cost-effective. We developed gender-specific indices to measure risk of HIV among sexually active individuals in Rakai, Uganda.We used multivariable Cox proportional hazards models to estimate time-to-HIV infection associated with candidate predictors. Reduced models were determined using backward selection procedures with Akaike's information criterion (AIC) as the stopping rule. Model discrimination was determined using Harrell's concordance index (c index). Model calibration was determined graphically. Nomograms were used to present the final prediction models.We used samples of 7,497 women and 5,783 men. 342 new infections occurred among females (incidence 1.11/100 person years,) and 225 among the males (incidence 1.00/100 person years). The final model for men included age, education, circumcision status, number of sexual partners, genital ulcer disease symptoms, alcohol use before sex, partner in high risk employment, community type, being unaware of a partner's HIV status and community HIV prevalence. The Model's optimism-corrected c index was 69.1 percent (95% CI = 0.66, 0.73). The final women's model included age, marital status, education, number of sex partners, new sex partner, alcohol consumption by self or partner before sex, concurrent sexual partners, being employed in a high-risk occupation, having genital ulcer disease symptoms, community HIV prevalence, and perceiving oneself or partner to be exposed to HIV. The models optimism-corrected c index was 0.67 (95% CI = 0.64, 0.70). Both models were well calibrated.These indices were discriminative and well calibrated. This provides proof-of-concept that population-based HIV risk indices can be developed. Further research to validate these indices for other populations is needed.

Disease aggressiveness remains a critical factor to the progression of prostate cancer. Transformation of epithelial cells to mesenchymal lineage, associated with the loss of E-cadherin, offers significant invasive potential and migration capability. Recently, Special AT-rich binding protein (SATB1) has been linked to tumor progression. SATB1 is a cell-type restricted nuclear protein, which functions as a tissue-specific organizer of DNA sequences during cellular differentiation. Our results demonstrate that SATB1 plays significant role in prostate tumor invasion and migration and its nuclear localization correlates with disease aggressiveness. Clinical specimen analysis showed that SATB1 was predominantly expressed in the nucleus of high-grade tumors compared to low-grade tumor and benign tissue. A progressive increase in the nuclear levels of SATB1 was observed in cancer tissues compared to benign specimens. Similarly, SATB1 protein levels were higher in a number of prostate cancer cells viz. HPV-CA-10, DU145, DUPro, PC-3, PC-3M, LNCaP and C4-2B, compared to non-tumorigenic PZ-HPV-7 cells. Nuclear expression of SATB1 was higher in biologically aggressive subclones of prostate cancer cells with their respective parental cell lines. Furthermore, ectopic SATB1 transfection conferred increased cell motility and invasiveness in immortalized human prostate epithelial PZ-HPV-7 cells which correlated with the loss of E-cadherin expression. Consequently, knockdown of SATB1 in highly aggressive human prostate cancer PC-3M cells inhibited invasiveness and tumor growth in vivo along with increase in E-cadherin protein expression. Our findings demonstrate that SATB1 has ability to promote prostate cancer aggressiveness through epithelial-mesenchymal transition.

There has been substantial growth in the numbers of patients with conjunctival squamous cell carcinoma infected with HIV in East Africa. The natural history of the conjunctival squamous cell carcinoma appears to be unique in this region of the world, but the etiologic mechanism unclear and therapeutic options limited. This research was carried out to determine if conjunctival squamous cell carcinoma harbors human papillomavirus DNA and is associated with activation of the EGFR signaling pathway. Positive findings would identify etiologic causes and provide clinical guidance to improve treatment.Expression of p-MAPK/MAPK, p-Akt/Akt and p-EGFR/EGFR in cell nuclei and cytoplasm of 38 FFPE specimens were assessed by immunohistochemistry; HPV genotype was detected by qPCR assay; EGFR mutation was assessed by DNA sequencing analysis; and EGFR mRNA expression was measured using relative qPCR. Statistical analyses included two-sided Fisher exact test or chi-square test, Spearman correlation coefficient and ANOVA. HPV 18 was found in 61% of samples, with HPV 16 double-genotype in 6 patients (16%). Immunohistochemistry and qPCR data suggest that activation and expression of the EGFR signaling pathway is related to disease progression of conjunctival cancer. The associations between cytoplasmic p-MAPK, cytoplasmic p-Akt and tumor invasiveness were significant (p = 0.05 or 0.028). Nuclear p-EGFR appeared only in invasive tumors. A significant positive association between EGFR expression and disease invasiveness was observed (p = 0.01). A SNP in 10 patients and one missense mutation were found within EGFR tyrosine kinase domain. Statistical analysis indicates that patients with measurable EGFR expression more likely harbor EGFR mutations, compared to those with negative EGFR expression (35.3% vs. 0%).We conclude that HPV types 16/18 infection is frequent in East African patients with AIDS-associated squamous cell carcinoma of the conjunctiva. EGFR activation/alteration may contribute to and sustain the high prevalence of this cancer. Our findings hint that adoption of HPV vaccination strategies may impact the incidence of conjunctival carcinoma. Agents that target the EGFR pathway may have potential therapeutic benefit.