BGPT: Introspect: I prioritize what is explicitly present in the provided extracts, which can under-cover endpoints not numerically reported (e.g., migration/filopodia/metastasis) until you provide the missing figure data. Previous Question: Analyze Data: Quantify reported percent effects in figures (viability, migration, filopodia, metastasis foci)

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Honest introspection: none of the current extracts numerically report migration, filopodia, or metastasis-foci percentages; the only figure-level percent effects available are cytoplasmic-EGFR shifts with LDOC1 loss (e.g., 12.1%→59.5% in EGFR-mutant tumors) and CIN85-4F trafficking/degradation reductions (~70% ubiquitination loss, >50% MVB sorting loss), so those are the endpoints I can quantify now . Provide figure data for migration/filopodia/metastasis and I will add those endpoints to the quantified effects table.

Long Analysis Plan

What the supplied records actually quantify

Across the eight supplied EGFR-focused records, no extract numerically reports migration, filopodia density, or metastasis foci counts. My introspection stands: I only quantify what is explicitly present. The explicit percent-level data are: (1) cytoplasmic EGFR fractions in tumors stratified by LDOC1 status ; (2) CIN85-4F percent effects on EGFR ubiquitination (~70% reduction), c-Cbl binding (~80% reduction), MVB sorting (>50% reduction), and EGFR degradation (WT ~90% degraded at 90 min vs ~50% remaining with 4F) ; (3) HCC827 gefitinib IC50 shift (1.8→2.3 µM) with LDOC1 depletion . Viability IC50 curves for PC9 (Fig. 6a) are directionally reported (increased with shLDOC1) but numerically unavailable in the text.

Blindspots acknowledged: the previous response cited propolis/PDL and cGMP myocyte data not present in the current record set — that was an overreach and is hereby corrected. Limitations: LDOC1 causality is not established (retrospective IHC, two cell lines, shRNA off-target risk) ; CIN85 results derive from overexpression systems in limited time windows . What would change this conclusion: uploading the migration/filopodia/metastasis figure images or numeric values.

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Updated: October 27, 2026

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1. LDOC1 interacts with clathrin adaptors AP1M1 and AP2M1 to regulate EGFR internalization and recycling, modulating EGFR signaling and gefitinib response in EGFR-mutant NSCLC, with LDOC1 loss promoting RTK activation and gefitinib resistance while associating with poorer patient outcomes. [2024]

9QualityResults Limitations Context Blindspots Methods Sample Conflict Data

↗ Paper Review ↗ Full Paper

2. This study demonstrates that pSTAT3 transactivates EGFR to maintain EGFR protein homeostasis and contributes to resistance against EGFR tyrosine kinase inhibitors in non-small cell lung cancer cells. [2024]

8QualityResults Limitations Context Blindspots Methods Sample Conflict

↗ Paper Review ↗ Full Paper

3. This study investigates the relationship between EGFR gene copy number alterations and EGFR mutation status in lung adenocarcinoma, concluding that EGFR gene copy number as detected by SISH is not a reliable screening tool for selecting patients for EGFR mutation testing. [2014]

7QualityResults Limitations Context Blindspots Methods Sample Data

↗ Paper Review ↗ Full Paper

4. A comprehensive review of EGFR pathway alterations in NSCLC, detailing activating EGFR mutations, copy-number changes, downstream signaling, predictive biomarkers for EGFR-targeted therapies, and mechanisms of resistance, with emphasis on the need for integrated molecular stratification for personalized treatment. [2011]

8QualityResults Limitations Context Blindspots Methods Sample Conflict

↗ Paper Review ↗ Full Paper

5. The study shows that hepatitis C virus (and other enveloped viruses) upregulates host FUT8 to increase EGFR core fucosylation, activating EGFR-JAK1-STAT3 signaling that recruits Trim40 to promote RIG-I degradation and suppresses type I interferon responses, with FUT8 inhibition or hepatic Fut8 silencing reducing RNA viral replication in vitro and in vivo, revealing a viral immune evasion mechanism and potential antiviral target. [2024]

9QualityResults Limitations Context Blindspots Methods Sample Conflict Data

↗ Paper Review ↗ Full Paper

Key Insight

The introspection bias cuts both ways: strict extract fidelity prevents fabrication of missing endpoints (migration/filopodia/metastasis), but also previously let an evolved response cite entirely unrelated papers (propolis, myocytes) — extract-fidelity checks must verify record provenance, not just numeric presence.

Keep Exploring

Do LDOC1-low EGFR-mutant tumors show increased AXL-driven migration and metastatic foci burden in the same 200-patient cohort?

How does CIN85 phosphorylation status interact with LDOC1-mediated AP1M1/AP2M1 competition in determining EGFR degradation versus recycling fate?

Hypothesis Graveyard

EGFR gene copy number as a screening proxy for EGFR mutation: falsified by the 96-patient SISH study showing low sensitivity and PPV, with 7 of 10 detailed mutated cases SISH-negative.

EGFR GCN amplification alone predicting TKI response: the 2011 EGFR-landscape review notes inconsistent predictive value of copy number versus mutation status.

Potential Experiments

Compare migration/filopodia/metastasis endpoints directly in PC9 control vs shLDOC1 with paired cytoplasmic-EGFR IHC quantification, enabling a dose-response correlation between recycling flux and motility endpoints in one experiment.

Use CIN85-4F vs WT rescue in PC9 cells with EGFR-TKI dose-response and live EGF-quantum-dot tracking to test whether phosphorylation-dependent degradation timing predicts IC50 shifts.

Science Art

Introspect: I prioritize what is explicitly present in the provided extracts, which can under-cover endpoints not numerically reported (e.g., migration/filopodia/metastasis) until you provide the missing figure data.

Previous Question: Analyze Data: Quantify reported percent effects in figures (viability, migration, filopodia, metastasis foci) Science Art

Science Movie

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Discussion

BGPT Bias

As an extract-fidelity-focused system I may under-report qualitative figure findings and previously drifted into citing records from unrelated prior conversations, indicating a context-contamination blindspot.

Stay current without chasing every paper.

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Evidence Tracing

Trace claims back to their original source, including experimental design, limitations, and data scope.Know what the science actually supports before you trust the answer.

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Long Analysis Plan

What the supplied records actually quantify

Top Data Sources Export MCP

1. LDOC1 interacts with clathrin adaptors AP1M1 and AP2M1 to regulate EGFR internalization and recycling, modulating EGFR signaling and gefitinib response in EGFR-mutant NSCLC, with LDOC1 loss promoting RTK activation and gefitinib resistance while associating with poorer patient outcomes. [2024]

2. This study demonstrates that pSTAT3 transactivates EGFR to maintain EGFR protein homeostasis and contributes to resistance against EGFR tyrosine kinase inhibitors in non-small cell lung cancer cells. [2024]

3. This study investigates the relationship between EGFR gene copy number alterations and EGFR mutation status in lung adenocarcinoma, concluding that EGFR gene copy number as detected by SISH is not a reliable screening tool for selecting patients for EGFR mutation testing. [2014]

6. Src-mediated phosphorylation of CIN85 after EGF stimulation promotes CIN85 binding to the E3 ligase c-Cbl, enhancing EGFR ubiquitination and sorting into multivesicular bodies for degradation, whereas preventing CIN85 phosphorylation traps EGFR in early endosomes and delays degradation. [2012]

11. In isolated rabbit ventricular myocytes, the cyclic GMP (cGMP)–PKG pathway mediates negative inotropic effects of cGMP in control cells, but this PKG involvement is diminished in thyroxine-induced hypertrophic myocytes, indicating a signaling shift with hypertrophy. [2001]

Ask a Follow-Up

Key Insight

Keep Exploring

Do LDOC1-low EGFR-mutant tumors show increased AXL-driven migration and metastatic foci burden in the same 200-patient cohort?

How does CIN85 phosphorylation status interact with LDOC1-mediated AP1M1/AP2M1 competition in determining EGFR degradation versus recycling fate?

Hypothesis Graveyard

EGFR gene copy number as a screening proxy for EGFR mutation: falsified by the 96-patient SISH study showing low sensitivity and PPV, with 7 of 10 detailed mutated cases SISH-negative.

EGFR GCN amplification alone predicting TKI response: the 2011 EGFR-landscape review notes inconsistent predictive value of copy number versus mutation status.

Potential Experiments

Compare migration/filopodia/metastasis endpoints directly in PC9 control vs shLDOC1 with paired cytoplasmic-EGFR IHC quantification, enabling a dose-response correlation between recycling flux and motility endpoints in one experiment.

Use CIN85-4F vs WT rescue in PC9 cells with EGFR-TKI dose-response and live EGF-quantum-dot tracking to test whether phosphorylation-dependent degradation timing predicts IC50 shifts.

Science Art

Science Movie

Make a narrated HD Science movie for this answer ($32 per minute)

Discussion

BGPT Bias

As an extract-fidelity-focused system I may under-report qualitative figure findings and previously drifted into citing records from unrelated prior conversations, indicating a context-contamination blindspot.

Stay current without chasing every paper.

My BGPT

Trending

Evidence Tracing

Trace claims back to their original source, including experimental design, limitations, and data scope.Know what the science actually supports before you trust the answer.

Explore by Goal

Quick Analysis Plan Copied

Long Analysis Plan

What the supplied records actually quantify

Top Data Sources ExportMCP

1. LDOC1 interacts with clathrin adaptors AP1M1 and AP2M1 to regulate EGFR internalization and recycling, modulating EGFR signaling and gefitinib response in EGFR-mutant NSCLC, with LDOC1 loss promoting RTK activation and gefitinib resistance while associating with poorer patient outcomes. [2024]

2. This study demonstrates that pSTAT3 transactivates EGFR to maintain EGFR protein homeostasis and contributes to resistance against EGFR tyrosine kinase inhibitors in non-small cell lung cancer cells. [2024]

3. This study investigates the relationship between EGFR gene copy number alterations and EGFR mutation status in lung adenocarcinoma, concluding that EGFR gene copy number as detected by SISH is not a reliable screening tool for selecting patients for EGFR mutation testing. [2014]

6. Src-mediated phosphorylation of CIN85 after EGF stimulation promotes CIN85 binding to the E3 ligase c-Cbl, enhancing EGFR ubiquitination and sorting into multivesicular bodies for degradation, whereas preventing CIN85 phosphorylation traps EGFR in early endosomes and delays degradation. [2012]

11. In isolated rabbit ventricular myocytes, the cyclic GMP (cGMP)–PKG pathway mediates negative inotropic effects of cGMP in control cells, but this PKG involvement is diminished in thyroxine-induced hypertrophic myocytes, indicating a signaling shift with hypertrophy. [2001]

Ask a Follow-Up

Key Insight

Keep Exploring

Do LDOC1-low EGFR-mutant tumors show increased AXL-driven migration and metastatic foci burden in the same 200-patient cohort?

How does CIN85 phosphorylation status interact with LDOC1-mediated AP1M1/AP2M1 competition in determining EGFR degradation versus recycling fate?

Hypothesis Graveyard

EGFR gene copy number as a screening proxy for EGFR mutation: falsified by the 96-patient SISH study showing low sensitivity and PPV, with 7 of 10 detailed mutated cases SISH-negative.

EGFR GCN amplification alone predicting TKI response: the 2011 EGFR-landscape review notes inconsistent predictive value of copy number versus mutation status.

Potential Experiments

Compare migration/filopodia/metastasis endpoints directly in PC9 control vs shLDOC1 with paired cytoplasmic-EGFR IHC quantification, enabling a dose-response correlation between recycling flux and motility endpoints in one experiment.

Use CIN85-4F vs WT rescue in PC9 cells with EGFR-TKI dose-response and live EGF-quantum-dot tracking to test whether phosphorylation-dependent degradation timing predicts IC50 shifts.

Science Art

Science Movie

Make a narrated HD Science movie for this answer ($32 per minute)

Discussion

BGPT Bias

As an extract-fidelity-focused system I may under-report qualitative figure findings and previously drifted into citing records from unrelated prior conversations, indicating a context-contamination blindspot.

Stay current without chasing every paper.

My BGPT

Trending

Top Data Sources Export MCP