01855nas a2200205 4500008004100000245011700041210006900158260000900227300000600236490000600242520110000248100003201348700002501380700003001405700001601435700001601451700003101467700002101498856013001519 2021 eng d00aIntegrated genetic and metabolic landscapes predict vulnerabilities of temozolomide resistant glioblastoma cells0 aIntegrated genetic and metabolic landscapes predict vulnerabilit cJAN  a20 v73 a

Metabolic reprogramming and its molecular underpinnings are critical to unravel the duality of cancer cell function and chemo-resistance. Here, we use a constraints-based integrated approach to delineate the interplay between metabolism and epigenetics, hardwired in the genome, to shape temozolomide (TMZ) resistance. Differential metabolism was identified in response to TMZ at varying concentrations in both the resistant neurospheroidal (NSP) and the susceptible (U87MG) glioblastoma cell-lines. The genetic basis of this metabolic adaptation was characterized by whole exome sequencing that identified mutations in signaling pathway regulators of growth and energy metabolism. Remarkably, our integrated approach identified rewiring in glycolysis, TCA cycle, malate aspartate shunt, and oxidative phosphorylation pathways. The differential killing of TMZ resistant NSP by Rotenone at low concentrations with an IC50 value of 5 nM, three orders of magnitude lower than for U87MG that exhibited an IC50 value of 1.8 mM was thus identified using our integrated systems-based approach.

1 aImmanuel, Selva, Rupa Chris1 aGhanate, Avinash, D.1 aParmar, Dharmeshkumar, S.1 aYadav, Ritu1 aUthup, Riya1 aPanchagnula, Venkateswarlu1 aRaghunathan, Anu uhttps://library.ncl.res.in/content/integrated-genetic-and-metabolic-landscapes-predict-vulnerabilities-temozolomide-resistant06441nas a2200865 4500008004100000245020100041210007000242260000800312490000700320520376100327100003104088700002604119700001804145700001804163700002504181700002604206700002004232700001904252700001604271700002104287700002704308700001904335700002204354700001904376700002604395700001904421700002004440700002104460700002004481700002004501700002304521700002404544700002204568700002504590700002704615700001804642700002004660700002104680700001604701700002004717700001504737700002904752700002104781700002104802700001904823700002704842700002904869700001804898700001804916700002604934700003204960700001904992700001905011700002005030700002305050700001605073700002205089700001905111700002005130700001605150700003105166700001605197700001805213700002505231700002105256700001505277700001905292700002005311700002405331700002805355700001705383700002005400700002005420856013505440 2024 eng d00aImmunogenicity of SARS-CoV-2 vaccines BBV152 (COVAXIN®) and ChAdOx1 nCoV-19 (COVISHIELD™) in seronegative and seropositive individuals in India: a multicentre, nonrandomised observational study0 aImmunogenicity of SARSCoV2 vaccines BBV152 COVAXIN® and ChAdOx1  cMAR0 v223 a

Background: There are limited global data on head-to-head comparisons of vaccine platforms assessing both humoral and cellular immune responses, stratified by pre-vaccination serostatus. The COVID-19 vaccination drive for the Indian population in the age group 18-45 years began in April 2021 when seropositivity rates in the general population were rising due to the delta wave of COVID-19 pandemic during April-May 2021.

Methods: Between June 30, 2021, and Jan 28, 2022, we enrolled 691 participants in the age group 18-45 years across four clinical sites in India. In this non-randomised and laboratory blinded study, participants received either two doses of Covaxin® (4 weeks apart) or two doses of Covishield™ (12 weeks apart) as per the national vaccination policy. The primary outcome was the seroconversion rate and the geometric mean titre (GMT) of antibodies against the SARS-CoV-2 spike and nucleocapsid proteins post two doses. The secondary outcome was the frequency of cellular immune responses pre- and post-vaccination.

Findings: When compared to pre-vaccination baseline, both vaccines elicited statistically significant seroconversion and binding antibody levels in both seronegative and seropositive individuals. In the per-protocol cohort, Covishield™ elicited higher antibody responses than Covaxin® as measured by seroconversion rate (98.3% vs 74.4%, p < 0.0001 in seronegative individuals; 91.7% vs 66.9%, p < 0.0001 in seropositive individuals) as well as by anti-spike antibody levels against the ancestral strain (GMT 1272.1 vs 75.4 binding antibody units/ml [BAU/ml], p < 0.0001 in seronegative individuals; 2089.07 vs 585.7 BAU/ml, p < 0.0001 in seropositive individuals). As participants at all clinical sites were not recruited at the same time, site-specific immunogenicity was impacted by the timing of vaccination relative to the delta and omicron waves. Surrogate neutralising antibody responses against variants-of-concern including delta and omicron was higher in Covishield™ recipients than in Covaxin® recipients; and in seropositive than in seronegative individuals after both vaccination and asymptomatic infection (omicron variant). T cell responses are reported from only one of the four site cohorts where the vaccination schedule preceded the omicron wave. In seronegative individuals, Covishield™ elicited both CD4+ and CD8+ spike-specific cytokine-producing T cells whereas Covaxin® elicited mainly CD4+ spike-specific T cells. Neither vaccine showed significant post-vaccination expansion of spike-specific T cells in seropositive individuals.

1 aAsokan, Mangaiarkarasi, S.1 aJoan, Roshni, Florina1 aBabji, Sudhir1 aDayma, Girish1 aNadukkandy, Prajitha1 aSubrahmanyam, Vinutha1 aPandey, Archana1 aMalagi, Girish1 aArya, Pooja1 aMahajan, Vibhuti1 aBhavikatti, Jayateerth1 aPawar, Ketakee1 aThorat, Aishwarya1 aShah, Priyanki1 aGoud, Ramakrishna, B.1 aRoy, Bishnudeo1 aRajukutty, Shon1 aImmanuel, Sushil1 aAgarwal, Dhiraj1 aSaha, Sankhanil1 aShivaraj, Akshatha1 aPanikulam, Patricia1 aShome, Rajeshwari1 aGulzar, Shah-E-Jahan1 aSharma, Anusmrithi, U.1 aNaik, Ajinkya1 aTalashi, Shruti1 aBelekar, Madhuri1 aYadav, Ritu1 aKhude, Poornima1 aV, Mamatha1 aShivalingaiah, Sudarshan1 aDeshmukh, Urmila1 aBhise, Chinmayee1 aJoshi, Manjiri1 aInbaraj, Leeberk, Raja1 aChandrasingh, Sindhulina1 aGhose, Aurnab1 aJamora, Colin1 aKarumbati, Anandi, S.1 aSundaramurthy, Varadharajan1 aJohnson, Avita1 aRamesh, Naveen1 aChetan, Nirutha1 aParthiban, Chaitra1 aAhmed, Asma1 aRakshit, Srabanti1 aAdiga, Vasista1 aD'souza, George1 aRale, Vinay1 aGeorge, Carolin, Elizabeth1 aJohn, Jacob1 aKawade, Anand1 aChaturvedi, Akanksha1 aRaghunathan, Anu1 aDias, Mary1 aBhosale, Anand1 aRaghu, Padinjat1 aShashidhara, L., S.1 ayakarnam, Annapurna, V.1 aBal, Vineeta1 aKang, Gagandeep1 aMayor, Satyajit uhttps://library.ncl.res.in/content/immunogenicity-sars-cov-2-vaccines-bbv152-covaxin%C2%AE-and-chadox1-ncov-19-covishield%E2%84%A202711nas a2200253 4500008004100000022001400041245012900055210006900184260000900253300001100262490000800273520181700281653002302098653002902121653001702150653001502167653003902182653002502221100002102246700002502267700001602292700002102308856012802329 2025 eng d a0006-291X00aIntegrated analysis of mitochondrial ETC inhibition reveals genotype-specific heterogeneity of drug response in glioblastoma0 aIntegrated analysis of mitochondrial ETC inhibition reveals geno cNOV  a1527980 v7873 a

Glioblastoma (GBM) is among the most aggressive brain cancers, driven by genetic diversity and resistance to therapy. Mitochondrial metabolism-and in particular the electron transport chain (ETC)-has emerged as both a key weakness and a source of variable drug response. To investigate this, we integrated constraint-based metabolic modeling (CBM), high-resolution drug profiling, and genomic sequencing across three GBM cell models: LN229, U87MG, and neurospheres (NSP). Modeling predicted distinct ETC vulnerabilities, which were confirmed experimentally using inhibitors against Complexes I-V. Sensitivity to rotenone varied sharply: NSP cells were most vulnerable (IC50 = 0.007 mu M), LN229 showed intermediate sensitivity (0.021 mu M), and U87MG remained highly resistant (1.816 mu M). Across inhibitors, LN229 consistently showed steep dose-response slopes, U87MG maintained flat curves, and NSP displayed selective weaknesses. By incorporating slope (m) and Instantaneous Inhibitory Potential (IIP), median-effect analysis captured dynamic drug-response behaviour's that IC50 values alone overlooked. Genomic sequencing revealed striking differences in mutational burden: U87MG and NSP carried 354 and 307 single nucleotide polymorphisms (SNPs), respectively, compared with 141 in LN229. Several non-synonymous mutations were directly linked to altered drug sensitivity, including L194S, Y50 N, and L46V in LN229; S456L, A466T, and Y629F in U87MG; and the NSP-specific R159Q. Notably, mutations near catalytic sites correlated with changes in slope and IIP, providing mechanistic insight into therapeutic response. Together, these results show how genetic variation reshapes ETC function and drug sensitivity in GBM, offering a predictive framework for mutation-informed, personalized therapy.

10aDrug dose response10aElectron transport chain10aGlioblastoma10aIC50 value10aInstantaneous inhibitory potential10aMitochondrial genome1 aBelekar, Madhuri1 aKavatalkar, Vijendra1 aYadav, Ritu1 aRaghunathan, Anu uhttps://library.ncl.res.in/content/integrated-analysis-mitochondrial-etc-inhibition-reveals-genotype-specific-heterogeneity