HIV+ Tumor Molecular Characterization Project - Diffuse Large B-Cell Lymphoma

Written and checked by a reviewer, not generated from metadata.

1. 1. How does the genomic landscape of HIV-associated diffuse large B-cell lymphoma differ from that of lymphoma in immunocompetent patients?

   Needs approved accessn ≈ 66HUMAN

   Whole genome sequencing on 66 cases from an HIV-enriched population, contrastable with the many DLBCL cohorts derived from largely HIV-negative populations. Whole genome rather than exome makes structural and viral-integration analysis possible.

   Statistical note: 70 cases supports description of recurrent alterations but not genome-wide discovery at conventional significance thresholds.

   NeedsWhole genome sequencingBulk RNA sequencing

2. 2. Does immune status shape the tumor transcriptome in lymphoma?

   Needs approved accessn ≈ 55HUMAN

   RNA sequencing on 55 cases with ECOG performance status on 71% allows transcriptional programs to be related to a clinical proxy for host status.

   Statistical note: ECOG is a crude proxy for immune competence; CD4 count would be far better and is not available in these records.

   NeedsBulk RNA sequencingClinical data

3. 3. What are the outcomes of HIV-associated DLBCL treated with standard regimens?

   Needs approved accessn ≈ 53HUMAN

   Vital status is informative for 76% of cases, follow-up is derivable for 57 of 70 with a median of 11.3 months extending to 99.6, and 24% carry a named regimen.

   Statistical note: 53 cases with informative vital status gives wide confidence intervals; median follow-up of 11.3 months is short for lymphoma outcomes.

   NeedsClinical dataOutcome dataTreatment records

Written by a reviewer against the source, not inferred from what is missing.

Articles that analyzed these data, counted separately from articles that only cited the paper. Only the first counts as reuse.

Analyses someone ran on these data end to end, each with a receipt recording when it ran, against which packages and for how long.

Starter code generated from this record’s own identifiers, then the access steps.

import json, requests

PROJECT = "CGCI-HTMCP-DLBCL"
filters = {"op": "and", "content": [
    {"op": "in", "content": {"field": "cases.project.project_id", "value": [PROJECT]}},
    {"op": "in", "content": {"field": "access", "value": ["open"]}},
]}
params = {"filters": json.dumps(filters),
          "fields": "file_id,file_name,data_category,data_type,file_size",
          "size": "10000", "format": "JSON"}
files = requests.get("https://api.gdc.cancer.gov/files", params=params, timeout=60).json()["data"]["hits"]
print(len(files), "open files")

# Write a manifest and fetch with the GDC client (https://gdc.cancer.gov/access-data/gdc-data-transfer-tool)
with open("manifest.txt", "w") as fh:
    fh.write("id\n" + "\n".join(f["file_id"] for f in files))
# $ gdc-client download -m manifest.txt

import json, requests

filters = {"op": "in", "content": {"field": "project.project_id", "value": ["CGCI-HTMCP-DLBCL"]}}
params = {"filters": json.dumps(filters), "size": "5000", "format": "TSV",
          "fields": ",".join([
              "submitter_id", "demographic.vital_status", "demographic.days_to_death",
              "diagnoses.days_to_last_follow_up", "diagnoses.ajcc_pathologic_stage",
              "diagnoses.treatments.treatment_type", "diagnoses.treatments.treatment_outcome"])}
tsv = requests.get("https://api.gdc.cancer.gov/cases", params=params, timeout=60).text
open("CGCI-HTMCP-DLBCL_clinical.tsv", "w").write(tsv)

from idc_index import IDCClient

COLLECTION = "cgci_htmcp_dlbcl"
client = IDCClient()

series = client.index[client.index["collection_id"] == COLLECTION]   # one row per DICOM series
print(len(series), "series,", series["PatientID"].nunique(), "patients,",
      round(series["series_size_MB"].sum() / 1024, 1), "GB")
print(series["Modality"].value_counts().to_dict())

# Everything above is an index lookup and costs nothing. Uncomment to pull the pixels;
# the client refuses up front if the disk cannot hold them.
# client.download_from_selection(collection_id=COLLECTION, downloadDir="./cgci_htmcp_dlbcl")

curl -s https://cd2s.vercel.app/data/datasets/gdc-cgci-htmcp-dlbcl.json | python3 -c '
import json, sys
r = json.load(sys.stdin)
for l in r["limitations"]:
    print(l["severity"].upper(), "-", l["statement"][:120])
print("survival endpoint:", r["longitudinal"]["has_survival_endpoint"], "| treatment response:", r["longitudinal"]["has_treatment_response"])'

Access steps

1. 1

   Scope with the 946 open-access filesFor people1 hour

   https://portal.gdc.cancer.gov/projects/CGCI-HTMCP-DLBCL
2. 2

   Request controlled access, naming HIV-related phenotype variablesFor peopledays to a few weeks

   Requires: eRA Commons account, institutional signing official approval

   https://gdc.cancer.gov/access-data/obtaining-access-controlled-data
3. 3

   Query the project from code, with no credentialsFor agents

   The file index is public even where files are not, so an agent can size the cohort before anyone requests access.

   curl -s 'https://api.gdc.cancer.gov/files' --get \
     --data-urlencode 'filters={"op":"in","content":{"field":"cases.project.project_id","value":["CGCI-HTMCP-DLBCL"]}}' \
     --data-urlencode 'fields=file_id,file_name,data_type' \
     --data-urlencode 'size=10000' --data-urlencode 'format=TSV'

   https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/

   Generated from repository policy. Check the linked policy before downloading.

4. 4

   Pass the token when the agent needs controlled filesFor agents

   Without a token, an API query may return only the open subset. Compare returned counts with the record before treating them as the whole cohort.

   Requires: GDC authentication token

   curl -H "X-Auth-Token: $GDC_TOKEN" https://api.gdc.cancer.gov/data/<file_id>

   https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/

   Generated from repository policy. Check the linked policy before downloading.

All of it, and more, is in this record’s JSON.

Same disease area, favoring cohorts that add a measurement this one lacks.