Salvage Using Polatuzumab Vedotin Based Therapy in Relapsed Refractory Large B-Cell Lymphomas: Early Experience from a Real-World Middle-Income Setting Using Named-Patient Compassionate Access Program.

Polatuzumab vedotin is a novel immunotherapy antibody-drug conjugate targeting CD79b. It has been used in relapsed/refractory (R/R) large B-cell lymphomas since its FDA approval in 2019. Presently, this drug is unaffordable or unavailable for patients in Lower-Middle Income Countries (LMIC) like India. This is a retrospective study of adult (> 18 years) patients with R/R large B-cell lymphoma failing two prior lines of therapy, who received Polatuzumab based salvage therapy on a compassionate or named-patient access program. Between May 2019 and April 2022, 10 patients received Polatuzumab vedotin, and 9 were evaluable. The most common regimen used was Polatuzumab-Bendamustine-Rituximab. Out of 43 infusions administered, the adverse event profile was manageable [One grade-2 infusion reaction, 4 patients developed grade 3-4 hematological toxicity and none had grade 3-4 non-hematological toxicities]. Ten infusions were administered in the day care service. After a median of 4.5 cycles (range 1-8), 4 patients achieved CR, 2 had partial response (PR), and 3 had progressive disease (PD). With a median follow up of 491 days (range 8-1048 days), four patients are alive (three in CR and one in PR), three patients have died and three patients were lost to follow up. Early real-world experience from a LMIC setting demonstrates feasibility and a favourable safety profile of Polatuzumab vedotin based approach, along with encouraging response rates in a subset of patients.

Cerium Phosphate-Cerium Oxide Heterogeneous Composite Nanozymes with Enhanced Peroxidase-Like Biomimetic Activity for Glucose and Hydrogen Peroxide Sensing.

In the present work, we focus on the development of CePO4-CeO2 composite nanorods with peroxidase mimetic activity for the sensitive detection of hydrogen peroxide and glucose. The Ce3+/PO43- molar ratio (CP10:1, CP5:1, CP2:1) in the hydrothermal reaction controlled the formation of pure CePO4, CePO4-CeO2 composite nanozymes with different percentages of CeO2, and its crystal structure. A higher Ce3+/PO43- molar ratio (CP10:1 or CP5:1) was required to obtain CePO4-CeO2 composite nanostructure, while a lower Ce3+/PO43- molar (CP2:1) ratio was sufficient to fabricate pure CePO4 nanorods. In the presence of hydrogen peroxide, the prepared nanozymes catalyze the oxidation of chromogenic substrate 3,3',5,5'-tetramethylbenzidine (TMB). Steady state kinetic analysis based on the Michaelis-Menten model revealed that CP10:1 showed excellent affinity toward the TMB ( Km = 0.236 mM and Vmax = 8.78 × 10-8 M s-1) in comparison to the catalytic activity of CP5:1 and CP2:1 and horseradish peroxidase ( Km = 0.434 mM and Vmax = 10.0 × 10-8 M s-1). The superior peroxidase activity of CePO4-CeO2 composite nanozymes can be ascribed to the enhanced redox switching between Ce3+ ↔ Ce4+ sites from the CePO4 and CeO2 lattice, respectively. The colorimetric detection of hydrogen peroxide and glucose showed a linear response around 150 µM concentration with the limits of detection (LOD) of 2.9 and 4.1 µM, respectively.

AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue.

In prognostic evaluation of breast cancer Immunohistochemical (IHC) markers namely, oestrogen receptor (ER) and progesterone receptor (PR) are widely used. The expert pathologist investigates qualitatively the stained tissue slide under microscope to provide the Allred score; which is clinically used for therapeutic decision making. Such qualitative judgment is time-consuming, tedious and more often suffers from interobserver variability. As a result, it leads to imprecise IHC score for ER and PR. To overcome this, there is an urgent need of developing a reliable and efficient IHC quantifier for high throughput decision making. In view of this, our study aims at developing an automated IHC profiler for quantitative assessment of ER and PR molecular expression from stained tissue images. We propose here to use CMYK colour space for positively and negatively stained cell extraction for proportion score. Also colour features are used for quantitative assessment of intensity scoring among the positively stained cells. Five different machine learning models namely artificial neural network, Naïve Bayes, K-nearest neighbours, decision tree and random forest are considered for learning the colour features using average red, green and blue pixel values of positively stained cell patches. Fifty cases of ER- and PR-stained tissues have been evaluated for validation with the expert pathologist's score. All five models perform adequately where random forest shows the best correlation with the expert's score (Pearson's correlation coefficient = 0.9192). In the proposed approach the average variation of diaminobenzidine (DAB) to nuclear area from the expert's score is found to be 7.58%, as compared to 27.83% for state-of-the-art ImmunoRatio software.

Imprint cytology-based breast malignancy screening: an efficient nuclei segmentation technique.

Imprint cytology (IC) refers to one of the most reliable, rapid and affordable techniques for breast malignancy screening; where shape variation of H&E stained nucleus is examined by the pathologists. This work aims at developing an automated and efficient segmentation algorithm by integrating Lagrange's interpolation and superpixels in order to delineate overlapped nuclei of breast cells (normal and malignant). Subsequently, a computer assisted IC tool has been designed for breast cancer (BC) screening. The proposed methodology consists of mainly three subsections: gamma correction for preprocessing, single nuclei segmentation and segmentation of overlapping nuclei. Single nuclei segmentation combines histogram-based thresholding and morphological operations; where segmentation of overlapping nuclei includes concave point detection, Lagrange's interpolation for overlapping arc area detection and the fine segmentation of overlapped arc area by superpixels. Total 16 significant features (p < 0.05) quantifying shape and texture of nucleus were extracted, and random forest (RF) classifier was skilled for automated screening. The proposed methodology has been tested on 120 IC images (approximately 12 000 nuclei); where 98% segmentation accuracy and 99% classification accuracy were achieved. Besides, performance evaluation was studied by using Jaccard's index (= 94%), correlation coefficient (= 95%), Dice similarity coefficient (= 97%) and Hausdorff distance (= 43%). The proposed approach could offer benefit to the pathologists for confirmatory BC screening with improved accuracy and could potentially lead to a better shape understanding of malignant nuclei.

MRF-ANN: a machine learning approach for automated ER scoring of breast cancer immunohistochemical images.

Molecular pathology, especially immunohistochemistry, plays an important role in evaluating hormone receptor status along with diagnosis of breast cancer. Time-consumption and inter-/intraobserver variability are major hindrances for evaluating the receptor score. In view of this, the paper proposes an automated Allred Scoring methodology for estrogen receptor (ER). White balancing is used to normalize the colour image taking into consideration colour variation during staining in different labs. Markov random field model with expectation-maximization optimization is employed to segment the ER cells. The proposed segmentation methodology is found to have F-measure 0.95. Artificial neural network is subsequently used to obtain intensity-based score for ER cells, from pixel colour intensity features. Simultaneously, proportion score - percentage of ER positive cells is computed via cell counting. The final ER score is computed by adding intensity and proportion scores - a standard Allred scoring system followed by pathologists. The classification accuracy for classification of cells by classifier in terms of F-measure is 0.9626. The problem of subjective interobserver ability is addressed by quantifying ER score from two expert pathologist and proposed methodology. The intraclass correlation achieved is greater than 0.90. The study has potential advantage of assisting pathologist in decision making over manual procedure and could evolve as a part of automated decision support system with other receptor scoring/analysis procedure.

Outcomes Following a Moderately Hypofractionated Adjuvant Radiation (START B Type) Schedule for Breast Cancer in an Unscreened Non-Caucasian Population.

AIMS: Breast cancer is the most common cancer in women. Western data have confirmed hypofractionated radiation therapy to be safe and effective in the adjuvant radiation therapy of breast cancers. We report the disease-related outcomes in a non-Caucasian, unscreened population treated with hypofractionated radiation. MATERIALS AND METHODS: Unselected case notes of patients presenting to a tertiary cancer centre between June 2011 and December 2013 were reviewed from the electronic hospital case records. Patients with a diagnosis of non-metastatic invasive non-sarcomatous breast cancer were identified. Demographic information, oestrogen receptor (ER), progesterone receptor (PR), HER2 status, pathological tumour, nodal stage at diagnosis and outcomes of treatment, including systemic therapies, surgery and hypofractionated radiation, were documented. Local recurrence rates, disease-free survival (DFS) and overall survival were calculated. RESULTS: Overall 925 patents were identified, median age 53.0 years (interquartile range 45-61), 330 of whom had neoadjuvant chemotherapy. The median follow-up time was 22.6 months and 23.5 months for overall and neoadjuvant chemotherapy groups, respectively. ER, PR and HER2 status was available in 788 patients, 77.2% of whom were ER/PR positive, 14.7% had triple negative disease, while 9.5% were HER2 rich. Overall, 34.2% (113 patients) underwent breast conservation surgery; 744 (80.4%) patients were treated with systemic chemotherapy and 878 (94.9%) patients received adjuvant radiation therapy, of whom 407 (44.0%) received supraclavicular-fossa radiotherapy. Overall survival, DFS and locoregional recurrence-free survival (LRRFS) for the overall group were 93%, 86.9% and 97.1%, respectively. LRRFS in the breast conservation surgery versus mastectomy groups were 99% versus 95.5% (P=0.003), with more node-positive patients in the mastectomy group. Stage N0/1 had better LRRFS compared with N2/2 (99.1% versus 95.7%); 94.3% versus 82.3%; P=0.005, 0.000. Grade 3 (53.8%) tumours had worse overall survival compared with grade 1 or grade 2 disease (89.6% versus 100% and 96.4%; P<0.001) although the LRRFS was not significantly different between the groups (98.9% versus 97.8%; P=0.37). There was no difference in LRRFS based on molecular subtypes. CONCLUSION: Local recurrence rates following hypofractionated radiation in our population were comparable with those reported by the START trialists and were found to be safe in the medium term for patients irrespective of breast conservation surgery/mastectomy or radiotherapy to the supraclavicular field. Molecular group frequencies were comparable with Western populations but did not affect LRRFS.