tooluniverse-cancer-classification

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Cancer Classification via OncoTree

基于OncoTree的癌症分类

Standardize cancer type nomenclature using the OncoTree ontology. Resolves free-text tumor descriptions to structured codes with UMLS/NCI cross-references, enabling downstream use in OncoKB variant annotation and GDC cohort selection.

使用OncoTree本体标准化癌症类型命名。将自由文本肿瘤描述解析为带有UMLS/NCI交叉引用的结构化代码，支持下游用于OncoKB变异注释和GDC队列筛选。

When to Use

适用场景

Apply when researcher asks about:

"What is the OncoTree code for [tumor description]?"
"Find all subtypes of [cancer type]"
"What cancers originate in [tissue]?"
"I need the tumor type code for OncoKB annotation"
"What is the TCGA/COSMIC code for [cancer]?"
"List all CNS/Brain cancer subtypes"
"What NCI code corresponds to glioblastoma?"

当研究人员提出以下问题时适用：

"[肿瘤描述]对应的OncoTree代码是什么？"
"查找[癌症类型]的所有亚型"
"哪些癌症起源于[组织]？"
"我需要用于OncoKB注释的肿瘤类型代码"
"[癌症]对应的TCGA/COSMIC代码是什么？"
"列出所有中枢神经系统/脑部癌症亚型"
"胶质母细胞瘤对应的NCI代码是什么？"

Key Tools

核心工具

Tool	Purpose	Key Params
`OncoTree_search`	Free-text search for cancer types	`query` (tumor name or description)
`OncoTree_get_type`	Full details for a known OncoTree code	`code` (e.g., "LUAD", "AML")
`OncoTree_list_tissues`	List all 32 tissue categories	(no params)
`OncoKB_annotate_variant`	Variant annotation using OncoTree code	`gene` , `variant` , `tumor_type`
`GDC_get_mutation_frequency`	Pan-cancer mutation frequency (TCGA)	`gene_symbol`

工具	用途	关键参数
`OncoTree_search`	癌症类型自由文本搜索	`query` （肿瘤名称或描述）
`OncoTree_get_type`	获取已知OncoTree代码的完整详情	`code` （例如："LUAD", "AML"）
`OncoTree_list_tissues`	列出全部32种组织类别	（无参数）
`OncoKB_annotate_variant`	使用OncoTree代码进行变异注释	`gene` , `variant` , `tumor_type`
`GDC_get_mutation_frequency`	泛癌突变频率（TCGA）	`gene_symbol`

Workflow

工作流程

Phase 1: Cancer Type Discovery

阶段1：癌症类型发现

Start with free-text search to find matching OncoTree codes:

OncoTree_search(query="breast cancer")
-> Returns list: code, name, main_type, tissue, parent, level, external_references

Key response fields:

```
code
```
: OncoTree code (e.g., "BRCA", "IBC") — use this in OncoKB calls
```
level
```
: hierarchy depth (1=tissue, 2=main type, 3-5=subtypes)
```
parent
```
: parent node code for navigating the hierarchy
```
external_references.UMLS
```
: UMLS CUI list
```
external_references.NCI
```
: NCI thesaurus code list

Search tips:

Broad terms ("lung cancer") return many results; narrow by tissue or level
Use tissue-specific terms ("invasive breast carcinoma") for precise matching
Acronyms work: query="GBM" finds glioblastoma, query="AML" finds leukemia types

首先通过自由文本搜索找到匹配的OncoTree代码：

OncoTree_search(query="breast cancer")
-> 返回列表：code, name, main_type, tissue, parent, level, external_references

关键响应字段：

```
code
```
: OncoTree代码（例如："BRCA", "IBC"）——用于OncoKB调用
```
level
```
: 层级深度（1=组织，2=主类型，3-5=亚型）
```
parent
```
: 用于导航层级结构的父节点代码
```
external_references.UMLS
```
: UMLS CUI列表
```
external_references.NCI
```
: NCI叙词表代码列表

搜索技巧：

宽泛术语（如"肺癌"）会返回大量结果；可通过组织或层级缩小范围
使用组织特异性术语（如"浸润性乳腺癌"）以获得精确匹配
缩写有效：query="GBM"会找到胶质母细胞瘤，query="AML"会找到白血病类型

Phase 2: Code Validation and Detail Retrieval

阶段2：代码验证与详情检索

Once you have a candidate code, retrieve full details:

OncoTree_get_type(code="LUAD")
-> Returns: name, main_type, tissue, color, parent, level, history, external_references

Note: Not all codes are valid. "GBM" returns 404 — correct code is "GB" (Glioblastoma, IDH-Wildtype). Always validate via

OncoTree_get_type

before using in downstream tools.

获得候选代码后，检索完整详情：

OncoTree_get_type(code="LUAD")
-> 返回：name, main_type, tissue, color, parent, level, history, external_references

注意：并非所有代码都有效。"GBM"会返回404——正确代码为"GB"（IDH野生型胶质母细胞瘤）。在下游工具中使用前，务必通过

OncoTree_get_type

进行验证。

Phase 3: Tissue-Level Exploration

阶段3：组织层级探索

When the user wants all cancers in a tissue category:

OncoTree_list_tissues()
-> Returns 32 tissue names: "Breast", "CNS/Brain", "Lung", "Myeloid", ...

OncoTree_search(query="CNS/Brain")
-> All cancer types with tissue="CNS/Brain"

当用户需要某一组织类别下的所有癌症时：

OncoTree_list_tissues()
-> 返回32种组织名称："Breast", "CNS/Brain", "Lung", "Myeloid", ...

OncoTree_search(query="CNS/Brain")
-> 所有tissue="CNS/Brain"的癌症类型

Phase 4: Downstream Use in Variant Annotation

阶段4：下游用于变异注释

Pass validated OncoTree code to OncoKB for cancer-type-specific therapeutic levels:

OncoKB_annotate_variant(gene="EGFR", variant="L858R", tumor_type="LUAD")
-> highestSensitiveLevel: "1" (FDA-approved therapy for this tumor+variant)

Without

tumor_type

, OncoKB returns pan-cancer levels which may be less specific.

将验证后的OncoTree代码传入OncoKB，获取癌症类型特异性治疗等级：

OncoKB_annotate_variant(gene="EGFR", variant="L858R", tumor_type="LUAD")
-> highestSensitiveLevel: "1"（针对该肿瘤+变异的FDA批准疗法）

若不传入

tumor_type

，OncoKB会返回泛癌等级，特异性可能不足。

Tool Parameter Reference

工具参数参考

Tool	Required	Optional	Notes
`OncoTree_search`	`query`	—	Free text; returns list sorted by relevance
`OncoTree_get_type`	`code`	—	Case-sensitive; "BRCA" not "brca". Returns 404 for invalid codes
`OncoTree_list_tissues`	—	—	No params; returns list of 32 tissue strings
`OncoKB_annotate_variant`	`gene` , `variant`	`tumor_type`	`tumor_type` is OncoTree code; omit for pan-cancer
`GDC_get_mutation_frequency`	`gene_symbol`	—	Pan-cancer TCGA only; no per-subtype breakdown

工具	必填参数	可选参数	说明
`OncoTree_search`	`query`	—	自由文本；返回按相关性排序的列表
`OncoTree_get_type`	`code`	—	区分大小写；"BRCA"而非"brca"。无效代码会返回404
`OncoTree_list_tissues`	—	—	无参数；返回32种组织字符串的列表
`OncoKB_annotate_variant`	`gene` , `variant`	`tumor_type`	`tumor_type` 为OncoTree代码；省略则返回泛癌结果
`GDC_get_mutation_frequency`	`gene_symbol`	—	仅支持TCGA泛癌；无亚型细分数据

Common OncoTree Codes (verified working)

常用有效OncoTree代码

Code	Name	Tissue
`BRCA`	Invasive Breast Carcinoma	Breast
`LUAD`	Lung Adenocarcinoma	Lung
`LUSC`	Lung Squamous Cell Carcinoma	Lung
`MEL`	Melanoma	Skin
`CRC`	Colorectal Cancer	Bowel
`PAAD`	Pancreatic Adenocarcinoma	Pancreas
`GBM`	(invalid — use `GB` )	CNS/Brain
`GB`	Glioblastoma, IDH-Wildtype	CNS/Brain
`AML`	Acute Myeloid Leukemia	Myeloid
`PRAD`	Prostate Adenocarcinoma	Prostate

代码	名称	组织
`BRCA`	浸润性乳腺癌	乳腺
`LUAD`	肺腺癌	肺
`LUSC`	肺鳞状细胞癌	肺
`MEL`	黑色素瘤	皮肤
`CRC`	结直肠癌	肠
`PAAD`	胰腺腺癌	胰腺
`GBM`	（无效——使用 `GB` ）	中枢神经系统/脑
`GB`	IDH野生型胶质母细胞瘤	中枢神经系统/脑
`AML`	急性髓系白血病	髓系
`PRAD`	前列腺腺癌	前列腺

Common Patterns

常用模式

python

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python

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Pattern: Resolve free-text to OncoTree code

模式：将自由文本解析为OncoTree代码

results = OncoTree_search(query="pancreatic ductal adenocarcinoma")

Pick result with lowest level number (most specific match)

选择层级编号最小的结果（最精确匹配）

code = results["data"][0]["code"] # e.g., "PAAD"

code = results["data"][0]["code"] # 例如："PAAD"

Pattern: Get all subtypes within a main type

模式：获取主类型下的所有亚型

results = OncoTree_search(query="Glioma") subtypes = [r for r in results["data"] if r["main_type"] == "Glioma"]

Pattern: Validate code before OncoKB call

模式：在调用OncoKB前验证代码

detail = OncoTree_get_type(code="GB") if detail["status"] == "success": OncoKB_annotate_variant(gene="IDH1", variant="R132H", tumor_type="GB")

undefined

detail = OncoTree_get_type(code="GB") if detail["status"] == "success": OncoKB_annotate_variant(gene="IDH1", variant="R132H", tumor_type="GB")

undefined

Tumor Classification Reasoning (CRITICAL)

肿瘤分类推理（至关重要）

LOOK UP DON'T GUESS -- tumor classification determines treatment. Always verify codes and biomarker interpretation via tools rather than relying on memory.

务必查询，切勿猜测——肿瘤分类决定治疗方案。始终通过工具验证代码和生物标志物解读，而非依赖记忆。

Histological vs Molecular Classification

组织学分类vs分子分类

Tumors are classified on TWO axes -- both matter for treatment selection:

Histological (what it looks like under microscope): adenocarcinoma, squamous, small cell, etc. This determines the OncoTree hierarchy level 3+.
Molecular (what mutations/alterations drive it): EGFR-mutant, HER2-amplified, MSI-high, etc. This determines OncoKB therapeutic levels.

A tumor can be histologically identical to another but molecularly different, requiring different treatment. Example: two lung adenocarcinomas (both LUAD) but one is EGFR-mutant (targeted therapy) and another is KRAS-mutant (different targeted therapy). Always check both axes.

肿瘤从两个维度进行分类——两者对治疗选择都至关重要：

组织学（显微镜下形态）：腺癌、鳞状细胞癌、小细胞癌等。决定OncoTree层级的3级及以上。
分子（驱动突变/改变）：EGFR突变型、HER2扩增型、MSI高表达型等。决定OncoKB治疗等级。两种肿瘤可能组织学相同但分子特征不同，需采用不同治疗方案。例如：两个肺腺癌（均为LUAD），一个是EGFR突变型（靶向治疗），另一个是KRAS突变型（不同靶向治疗）。务必同时检查两个维度。

Biomarker Interpretation Strategy

生物标志物解读策略

When interpreting cancer biomarkers, use OncoKB for actionability:

HER2: Positive = IHC 3+ or FISH-amplified. Use

OncoKB_annotate_variant(gene="ERBB2", variant="Amplification", tumor_type="BRCA")

for therapeutic level

ER/PR: Positive = hormone-receptor positive breast cancer. Changes treatment class (endocrine therapy)
Ki67: Proliferation index. High (>20%) suggests aggressive biology; used in breast cancer grading (Luminal A vs B)
TMB (Tumor Mutational Burden): High TMB (>10 mut/Mb) predicts immunotherapy response across tumor types. Use
```
OncoKB_annotate_variant(gene="Other Biomarkers", variant="TMB-H")
```
MSI (Microsatellite Instability): MSI-High is FDA-approved biomarker for pembrolizumab pan-cancer. Use
```
OncoKB_annotate_variant(gene="Other Biomarkers", variant="MSI-H")
```

解读癌症生物标志物时，使用OncoKB评估临床实用性：

HER2：阳性=IHC 3+或FISH扩增。使用

OncoKB_annotate_variant(gene="ERBB2", variant="Amplification", tumor_type="BRCA")

获取治疗等级

ER/PR：阳性=激素受体阳性乳腺癌。会改变治疗类别（内分泌治疗）
Ki67：增殖指数。高表达（>20%）提示侵袭性生物学特征；用于乳腺癌分级（ Luminal A vs B）
TMB（肿瘤突变负荷）：高TMB（>10 mut/Mb）可预测跨肿瘤类型的免疫治疗响应。使用
```
OncoKB_annotate_variant(gene="Other Biomarkers", variant="TMB-H")
```
MSI（微卫星不稳定性）：MSI高表达是帕博利珠单抗泛癌适应症的FDA批准生物标志物。使用
```
OncoKB_annotate_variant(gene="Other Biomarkers", variant="MSI-H")
```

Staging vs Grading -- Different Concepts

分期vs分级——不同概念

Stage (TNM): How far has it spread? T=tumor size, N=lymph nodes, M=metastasis. Stage I-IV. Determines prognosis and surgery eligibility.
Grade: How abnormal do the cells look? Grade 1 (well-differentiated, slow) to Grade 3 (poorly-differentiated, aggressive). Determines aggressiveness.
A Stage I, Grade 3 tumor (small but aggressive) has different implications than Stage III, Grade 1 (spread but slow-growing).

分期（TNM）：肿瘤扩散程度？T=肿瘤大小，N=淋巴结，M=转移。分期I-IV。决定预后和手术资格。
分级：细胞形态异常程度？分级1（高分化，生长缓慢）至分级3（低分化，侵袭性强）。决定侵袭性。
I期3级肿瘤（体积小但侵袭性强）与III期1级肿瘤（已扩散但生长缓慢）的临床意义不同。

Actionability Assessment

实用性评估

After classifying the tumor, assess whether findings are clinically actionable:

Level 1 (FDA-approved, specific tumor type): Immediate treatment implication. Example: EGFR L858R in LUAD
Level 2 (Standard care): Strong evidence but context-dependent
Level 3 (Compelling evidence): Clinical trial candidates
Level 4 (Biological evidence): Research-stage only
Always provide the OncoTree code to OncoKB -- without it, you get pan-cancer levels which may understate or overstate actionability for the specific tumor type

分类肿瘤后，评估结果是否具有临床实用性：

1级（FDA批准，特定肿瘤类型）：直接指导治疗。例如：LUAD中的EGFR L858R突变
2级（标准治疗）：证据充分但需结合临床场景
3级（有力证据）：临床试验候选者
4级（生物学证据）：仅处于研究阶段
务必向OncoKB提供OncoTree代码——若无该代码，将返回泛癌等级，可能无法准确反映特定肿瘤类型的实用性

Reasoning Framework for Result Interpretation

结果解读推理框架

Evidence Grading

证据分级

Grade	Criteria	Example
Confirmed	Exact OncoTree code validated via `OncoTree_get_type` , UMLS + NCI cross-refs present	LUAD: validated, UMLS C0152013, NCI C3512
Probable	OncoTree search returns match, but code not yet validated or missing cross-refs	Search for "cholangiocarcinoma" returns CHOL with partial external refs
Ambiguous	Multiple OncoTree codes match the description at different hierarchy levels	"Breast cancer" matches BRCA (invasive), BREAST (tissue), IBC (inflammatory)
Unresolved	No OncoTree match; tumor type too rare or novel for the ontology	Ultra-rare sarcoma subtype not in OncoTree

等级	标准	示例
确认	精确的OncoTree代码已通过 `OncoTree_get_type` 验证，且存在UMLS + NCI交叉引用	LUAD：已验证，UMLS C0152013，NCI C3512
可能	OncoTree搜索返回匹配结果，但代码尚未验证或缺少交叉引用	搜索"胆管癌"返回CHOL，仅部分外部引用
模糊	多个OncoTree代码在不同层级匹配描述	"乳腺癌"匹配BRCA（浸润性）、BREAST（组织）、IBC（炎性）
未解决	无OncoTree匹配结果；肿瘤类型过于罕见或新颖，未纳入本体	超罕见肉瘤亚型未收录于OncoTree

Interpretation Guidance

解读指南

OncoTree code confidence: Always validate candidate codes with
```
OncoTree_get_type
```
before downstream use. Some common acronyms (e.g., "GBM") are NOT valid OncoTree codes (correct code is "GB"). A validated code with UMLS and NCI cross-references is highest confidence.
UMLS/NCI cross-reference priority: For standardized reporting, NCI Thesaurus codes are preferred for cancer-specific contexts (used by caDSR, GDC). UMLS CUIs are broader (cross-disease) and useful for literature mining. When both are available, report both; when only one exists, NCI is preferred for oncology workflows.
Tissue hierarchy interpretation: OncoTree levels represent specificity: Level 1 = tissue of origin (e.g., "Lung"), Level 2 = main cancer type (e.g., "Non-Small Cell Lung Cancer"), Level 3+ = histological subtypes (e.g., "Lung Adenocarcinoma"). For OncoKB variant annotation, use the most specific (deepest) level that accurately describes the tumor. For cohort-level analysis (e.g., TCGA), the Level 2-3 code is typically appropriate.
OncoKB tumor type impact: Providing a tumor type code to OncoKB can change the therapeutic level (e.g., EGFR L858R is Level 1 in LUAD but Level 3B pan-cancer). Always use the validated OncoTree code for the patient's specific tumor type.
Deprecated or renamed codes: OncoTree evolves across versions. The
```
history
```
field in
```
OncoTree_get_type
```
response shows prior names. Always use the current code.

OncoTree代码可信度：在下游使用前，务必通过
```
OncoTree_get_type
```
验证候选代码。部分常见缩写（如"GBM"）并非有效的OncoTree代码（正确代码为"GB"）。带有UMLS和NCI交叉引用的已验证代码可信度最高。
UMLS/NCI交叉引用优先级：对于标准化报告，NCI叙词表代码在癌症特定场景中更受青睐（被caDSR、GDC使用）。UMLS CUI范围更广（跨疾病），适用于文献挖掘。若两者均存在，同时报告；若仅存在其一，肿瘤学工作流优先使用NCI代码。
组织层级解读：OncoTree层级代表特异性：1级=起源组织（例如："肺"），2级=主癌症类型（例如："非小细胞肺癌"），3级及以上=组织学亚型（例如："肺腺癌"）。对于OncoKB变异注释，使用最能准确描述肿瘤的最具体（最深层）层级代码。对于队列分析（如TCGA），通常使用2-3级代码。
OncoKB肿瘤类型影响：向OncoKB提供肿瘤类型代码可能改变治疗等级（例如：EGFR L858R在LUAD中为1级，但泛癌为3B级）。始终使用患者特定肿瘤类型的已验证OncoTree代码。
已弃用或重命名的代码：OncoTree版本迭代会更新代码。
```
OncoTree_get_type
```
响应中的
```
history
```
字段显示曾用名。始终使用当前有效代码。

Synthesis Questions

综合问题

Does the chosen OncoTree code represent the most specific histological subtype, or could a more precise code provide better therapeutic annotation in OncoKB?
When the free-text tumor description maps to multiple OncoTree codes, which hierarchy level best balances specificity and coverage for the analysis goal (variant annotation vs cohort selection)?
Are the UMLS/NCI cross-references consistent with external classifications (WHO, ICD-O), or are there discrepancies that need resolution?

所选OncoTree代码是否代表最具体的组织学亚型？是否有更精确的代码能在OncoKB中提供更好的治疗注释？
当自由文本肿瘤描述匹配多个OncoTree代码时，哪个层级最能平衡分析目标（变异注释vs队列筛选）的特异性和覆盖范围？
UMLS/NCI交叉引用是否与外部分类标准（WHO、ICD-O）一致？是否存在需要解决的差异？

Fallback Chains

备选流程链

Primary	Fallback	When
`OncoTree_get_type(code="GBM")`	`OncoTree_search(query="glioblastoma")`	404 for common aliases
`OncoTree_search` (no results)	`OncoTree_list_tissues` + tissue-level search	Very rare/novel tumor types
OncoTree code for OncoKB	Omit `tumor_type` param	Code not recognized by OncoKB

主流程	备选流程	触发场景
`OncoTree_get_type(code="GBM")`	`OncoTree_search(query="glioblastoma")`	常见别名返回404
`OncoTree_search` （无结果）	`OncoTree_list_tissues` + 组织层级搜索	罕见/新型肿瘤类型
OncoTree代码用于OncoKB	省略 `tumor_type` 参数	OncoKB不识别该代码