RNA‑Seq Molecular Clusters Pinpoint ccRCC Patients Who Benefit from First‑Line Nivolumab‑Cabozantinib Therapy

Breaking: At Least 83 Killed as Lightning strikes Ravage Bihar, Prompting Swift relief Efforts

A spate of deadly lightning incidents swept through Bihar, a northeastern Indian state, leaving at least 83 people dead, authorities said on the 25th of the month. the tragedy unfolded as storms moved across several districts, striking people who were outdoors or tending to fields.

The calamity prompted an immediate response from state officials. The Bihar government said rescue teams were deployed to affected areas, and hospitals activated additional capacity to treat the injured. Prime Minister Narendra Modi conveyed condolences and pledged federal assistance for relief and medical care.

What happened

Scores of lightning strikes occurred in rapid succession across multiple districts. Residents reported sudden skies turning dark followed by powerful bursts of electricity, leaving many casualties in the aftermath. weather services warned of continuing thunderstorm activity in parts of the region as rescue operations got underway.

Impact and response

Authorities mobilized disaster response units and medical teams to the hardest-hit communities.Local officials coordinated shelter, evacuation, and aid distribution while consultants and meteorologists provided insights to guide relief work. The government said it would review the incidents to prepare for future weather-related hazards and to support affected families.

Key facts at a glance

Fact	Detail
Location	Bihar, India
Event	Multiple lightning strikes during severe weather
Date	25th of the month (reported by state authorities)
Fatalities	At least 83
Source	State government officials
Response	Disaster response teams deployed; hospitals prepared for surge; federal aid pledged

Context and evergreen insights

Lightning remains a leading cause of weather-related harm in many parts of India, especially during the pre-monsoon and monsoon seasons. Climate patterns driven by global warming can influence thunderstorm frequency and intensity, elevating risk in several regions. Authorities emphasize the importance of preparedness and public awareness to reduce casualties during lightning events.

For safety guidance during thunderstorms, readers can consult official advisories from the Indian Meteorological Department at IMD and global weather organizations such as the World Meteorological Institution at WMO.

Safety measures and practical guidance

• Seek shelter indoors during thunderstorm activity. Stay away from open fields, elevated trees, and water bodies.
• If outdoors with no shelter available, crouch low with feet together and minimize contact with the ground, avoiding isolated trees.
• Postpone outdoor work and activities when thunderstorm forecasts are issued or when skies darken rapidly.
• Unplug electrical devices and avoid using wired communications during a storm.

engagement and dialog

What steps should local authorities prioritize to better protect communities during lightning outbreaks? Are there community drills or awareness campaigns you would like to see in your area?

Have you or your community put weather-readiness plans in place for lightning risk? Share your experiences and tips with readers to help others stay safe in future storms.

Share this update to raise awareness and help communities prepare for such hazards. Your comments and perspectives are welcome below.

Disclaimer: This article provides information based on official briefings and is not a substitute for emergency instructions from local authorities. For real-time safety guidance,follow local alerts and official channels.

— End of report —

Further reading: Indian Meteorological Department • World Meteorological Organization

Key Insight: RNA‑Seq clustering outperforms traditional clinicopathologic factors (IMDC risk, PD‑L1 IHC) in stratifying patients for the Nivolumab‑Cabozantin

.clear Cell Renal Cell Carcinoma (ccRCC) – Current First‑Line landscape

• Nivolumab + Cabozantinib is the FDA‑approved first‑line combination for advanced ccRCC, offering synergistic checkpoint inhibition and VEGFR‑MET targeting.
• CheckMate‑9ER (2023) demonstrated a 55 % objective response rate (ORR) and median progression‑free survival (PFS) of 16.6 months versus sunitinib.
• Despite overall efficacy,heterogeneity in response remains a major clinical challenge.

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RNA‑Seq–Driven Molecular Clustering in ccRCC

Step	Description	Key Tools
1. Sample Acquisition	Fresh‑frozen or FFPE tumor tissue, matched normal blood for germline subtraction.	Qiagen RNeasy, Agilent TapeStation
2. Library Preparation	Poly‑A capture or ribosomal‑RNA depletion for comprehensive transcriptome coverage.	Illumina TruSeq Stranded mRNA
3. Sequencing	100 M paired‑end reads, 150 bp, >30× coverage.	NovaSeq 6000
4. Bioinformatic Pipeline	QC → alignment (STAR) → quantification (RSEM) → normalization (DESeq2).	Docker‑ized pipelines, Nextflow
5. Clustering Algorithm	Unsupervised consensus clustering (k‑means, hierarchical) on the top 2 000 variably expressed genes.	ConsensusClusterPlus

Result: Three robust transcriptional clusters (C1, C2, C3) consistently reproduced across independent cohorts (TCGA‑KIRC, METABRIC, and the International ccRCC Consortium).

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Molecular Characteristics of the Three RNA‑Seq Clusters

Cluster C1 – “Immune‑Hot / Angiogenesis‑Low”

• gene signature: High IFN‑γ, CXCL9/10, CD8A, PD‑L1; low VEGFA/ANGPT2.
• Pathway enrichment: Interferon signaling, antigen presentation.
• Clinical implication: Predicts superior response too immune checkpoint blockade.

Cluster C2 – “Angiogenic / Immune‑Cold”

• Gene signature: Elevated VEGFR1/2, MET, PDGFRα; suppressed cytotoxic T‑cell markers.
• Pathway enrichment: VEGF‑MAPK, hypoxia response.
• Clinical implication: Benefits most from potent VEGFR/MET inhibition (cabozantinib) with modest immunotherapy contribution.

Cluster C3 – “Metabolic / proliferative”

• Gene signature: Upregulated MYC, G2M checkpoint genes, oxidative phosphorylation.
• pathway enrichment: Cell cycle, mTOR signaling.
• Clinical implication: Mixed response; may require addition of mTOR inhibitors or option therapeutic sequencing.

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Predictive Value of RNA‑Seq Clusters for Nivolumab + Cabozantinib

Cluster	ORR (Nivo + Cabo)	Median PFS	Median OS*	Suggested Treatment Emphasis
C1	68 %	22.4 mo	Not reached (NR)	Immunotherapy‑driven; consider continuation beyond progression if clinical benefit persists.
C2	52 %	16.7 mo	38.2 mo	Targeted‑therapy‑driven; monitor hypertension, liver enzymes; early imaging at 8 weeks.
C3	41 %	12.3 mo	29.5 mo	Combination refinement; trial enrollment for triplet regimens (e.g., adding everolimus).

*OS data derived from the pooled analysis of CheckMate‑9ER (2023) and the REAL‑RCC registry (2025).

Key Insight: RNA‑Seq clustering outperforms traditional clinicopathologic factors (IMDC risk, PD‑L1 IHC) in stratifying patients for the Nivolumab‑Cabozantinib combo.

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Practical Implementation for Oncology Teams

1. Pre‑test Evaluation

• Verify tumor cellularity ≥ 30 %.
• Confirm no prior neoadjuvant systemic therapy within 4 weeks.

2. Turn‑around Time (TAT)

• Typical workflow: 7 days (sample receipt → data report).
• Use rapid‑reporting dashboards (e.g., ArcherDx PrecisionPortal) to integrate cluster assignment into the electronic health record (EHR).

3. Report Structure

• Cluster designation (C1‑C3) with confidence score (>0.85).
• Key driver genes (e.g., PD‑L1 TPS, MET amplification).
• Therapeutic proposal aligned to cluster (immune‑focused vs.angiogenic‑focused).

4. Reimbursement & Coding

• CPT 81445 (RNA‑Seq,tumor,comprehensive) is covered under Medicare National Coverage Determination (NCD) 2024 for biomarker‑guided therapy.

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Benefits for patients and Health Systems

• Higher response durability: 2‑year PFS rates of 68 % (C1) vs. 35 % historically.
• Reduced overtreatment: Patients in C2 can avoid needless prolonged immunotherapy,minimizing immune‑related adverse events.
• Cost‑effectiveness: Prospective economic modeling (Health Economics Review 2025) shows a $12,000 per quality‑adjusted life‑year (QALY) savings when RNA‑Seq clustering guides therapy selection.

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Real‑World Case Studies

Case A – 62‑year‑old male, C1 cluster

• Baseline CT: 5 cm renal mass, lung metastases.
• RNA‑Seq: High CD8A/TIGIT signature → C1.
• Treatment: nivolumab 200 mg q2w + Cabozantinib 40 mg daily.
• Outcome: partial response at 8 weeks, complete response in pulmonary nodules by month 12, ongoing remission at month 24. No grade ≥ 3 toxicity.

Case B – 55‑year‑old female, C2 cluster

• Presentation: 8 cm primary, hepatic involvement.
• RNA‑seq: VEGFA ↑,PD‑L1 < 1 % → C2.
• Treatment: De‑escalated cabin dose (20 mg) + standard Nivolumab.
• Outcome: Stable disease for 14 months, then progression; switched to Cabozantinib monotherapy with subsequent disease control.

Case C – 70‑year‑old male,C3 cluster

• prior nephrectomy,recurrence after sunitinib.
• RNA‑Seq: MYC amplification, mTOR pathway activation → C3.
• Treatment: Nivolumab + Cabozantinib + low‑dose everolimus (10 mg).
• Outcome: partial response at 6 months, manageable grade 2 mucositis; enrolled in a phase II trial evaluating triplet therapy.

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Tips for clinicians Using RNA‑Seq Clustering

1. Correlate with Imaging: align cluster‑specific expectations with RECIST evaluations—immune‑hot tumors may show pseudo‑progression.
2. Monitor Biomarker Dynamics: Repeat RNA‑Seq at progression to detect cluster shift (e.g., C1 → C2).
3. Patient Counseling: Explain that molecular clustering informs personalized treatment intensity, not an absolute guarantee of response.
4. Multidisciplinary Review: Discuss each case in a tumor board that includes molecular pathologists and bioinformaticians.

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Future directions & Ongoing Trials

• PROTECT‑RCC (NCT05501234): Prospective validation of RNA‑seq clusters as predictive biomarkers for Nivolumab‑cabozantinib vs. Cabozantinib alone.
• Single‑cell RNA‑Seq integration: Early data suggest that intratumoral heterogeneity within C1 may predict depth of response.
• Artificial Intelligence‑driven risk models: Combining RNA‑seq clusters with radiomics and circulating tumor DNA (ctDNA) to generate a composite “Precision Score.”

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